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- Vorburger, Audrey, et al.
(författare)
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Three‐Dimensional Modeling of Callisto's Surface Sputtered Exosphere Environment
- 2019
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Ingår i: Journal of Geophysical Research - Space Physics. - 2169-9380 .- 2169-9402. ; 124:8, s. 7157-7169
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Tidskriftsartikel (refereegranskat)abstract
- We study the release of various elements from Callisto's surface into its exosphere by plasma sputtering. The cold Jovian plasma is simulated with a 3‐D plasma‐planetary interaction hybrid model, which produces 2‐D surface precipitation maps for magnetospheric H+, O+, O++, and S++. For the hot Jovian plasma, we assume isotropic precipitation onto the complete spherical surface. Two scenarios are investigated: one where no ionospheric shielding takes place and accordingly full plasma penetration is implemented (no‐ionosphere scenario) and one where an ionosphere lets virtually none of the cold plasma but all of the hot plasma reach Callisto's surface (ionosphere scenario). In the 3‐D exosphere model, neutral particles are sputtered from the surface and followed on their individual trajectories. The 3‐D density profiles show that whereas in the no‐ionosphere scenario the ram direction is favored, the ionosphere scenario produces almost uniform density profiles. In addition, the density profiles in the ionosphere scenario are reduced by a factor of ∼2.5 with respect to the no‐ionosphere scenario. We find that the Neutral Gas and Ion Mass Spectrometer, which is part of the Particle Environment Package on board the JUpiter ICy moons Explorer mission, will be able to detect the different sputter populations from Callisto's icy surface and the major sputter populations from Callisto's nonicy surface. The chemical composition of Callisto's exosphere can be directly linked to the chemical composition of its surface and will offer us information not only on Callisto's formation scenario but also on the building blocks of the Jupiter system.
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- Wang, Leizhen, et al.
(författare)
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Data-driven analysis and modeling of individual longitudinal behavior response to fare incentives in public transport
- 2023
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Ingår i: Transportation. - : Springer Nature. - 0049-4488 .- 1572-9435.
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Tidskriftsartikel (refereegranskat)abstract
- Incentive-based public transport demand management (PTDM) can effectively mitigate overcrowding issues in crowded urban rail systems. Analyzing passengers’ behavioral responses to the incentive can guide the design, implementation, and update of PTDM strategies. Though several studies reported passengers’ responses to fare incentives, they focused on passengers’ short-term behavioral responses. Limited studies explore passengers’ longitudinal behavioral responses for different types of adopters, which is important for policy assessment and adjustment. This paper explores and models passengers’ longitudinal behavior response to a pre-peak fare discount incentive using 18 months of smartcard data in public transport in Hong Kong. We classified adopters into six types based on their temporal travel pattern changes before and after the promotion. The longitudinal analysis reveals that among all adopters, 19% of users change their departure times to take advantage of fare discounts but do not contribute to the goal of reducing peak-hour travel. However, these adopters are more likely to sustain their changed behavior in a long term which is not desired by the incentive program. The spatial analysis shows that the origin station distribution of late adopters is relatively more diverse than the early adopters with more trips starting from distant areas. The diffusion modeling shows that the majority adopters are innovators and the word-of-mouth diffusion effect (imitators) is marginal. The discrete choice model results highlight the heterogeneous impact of factors on different types of adopters and their values of time changes. The significant factors common to adopters are: departure time flexibility, the expected money savings, the required departure time changes, and work locations. The findings are useful for public transport planners and policymakers for informed incentive design and management.
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