Urban flooding alters travel behavior in coastal communities, yet few studies jointly examine multiple trip purposes, warning channels, and normal–flood mode choice. This study analyzes travel responses to flood scenarios using resident surveys, discrete choice modeling, and elasticity analysis. Overall trip rates declined, with discretionary and educational travel showing the steepest reductions, while essential trips such as work and shopping were largely retained but often delayed. Flooding increases travel times across all trip purposes, with smaller delays for work trips and moderate disruptions for shopping and non-home-based discretionary travel. Mode choice behavior shows reduced driving alone and greater use of carpooling and public transportation. Under normal conditions, travel is shaped by income, vehicle ownership, and employment, but during flooding, flood warnings and temporal flexibility become dominant. Interaction and elasticity results show that information access and adaptability drive resilient mobility decisions, informing adaptive transportation planning.
In this study, an inertia dynamometer test bench system fully compliant with united nations global technical regulation No. 24 (UN GTR-24) and Euro 7 regulations was employed to systematically evaluate brake wear particle (BWP) emissions from a pure electric light-duty passenger vehicle. A critical temperature window was identified for brake emissions, beyond which PN10 emissions increase sharply, ranging from 107.8 to 131.8 ℃ for the low-metallic (LM) material and from 106.4 to 135.1 ℃ for the non-asbestos organic (NAO) material. The uncorrected full-vehicle PM2.5 and PM10 emission factors are 2.459 and 4.576 mg/km/vehicle, respectively. After applying the UN GTR-24 correction factor (0.17) for regenerative braking in pure electric vehicles, the corrected PM2.5 and PM10 values become 0.418 and 0.778 mg/km/vehicle, which are well below the Euro 7 PM10 limit of 3 mg/km/vehicle. Transient PN10 emissions correlate strongly with brake disc temperature. Aggressive driving conditions (deceleration > 1.5 m/s2) trigger the highest PN10 peaks, primarily driven by rapid temperature rise.
Flood risk management often prioritizes roads by hazard exposure alone, overlooking the network-wide consequences of localized failures. This study quantifies how flood exposure and topological importance determine systemic disruption in Dhaka, Bangladesh. Integrating a stacking ensemble machine learning model trained on an 11-year Sentinel-1 SAR flood inventory with graph-theoretic network analysis, we demonstrate that flood susceptibility and betweenness centrality are significantly but weakly associated. A composite Critical Score shows vulnerability is highly concentrated, with the top 5% of segments holding 82.6% of the network total, but only partly clustered: these segments span 143 of 187 communities, and just 43.7% lie in LISA HH hotspots. Their failure fragments the network, raising origins without hospital access 73-fold. Flood-risk-weighted Leiden detection identifies 187 vulnerability zones, where the top ten concentrate 29.1% of total vulnerability in 7.0% of segments. This framework guides limited resilience investments toward infrastructure whose failure causes the greatest city-wide disruption.
This study evaluates the economic and regulatory performance of fatty acid methyl ester (FAME)-based drop-in biofuels under the EU Emissions Trading System (EU ETS), FuelEU Maritime, and the proposed IMO Net-Zero Framework (NZF). A container ship is analyzed over 2028–2040 under three compliance pathways: reference, minimum-cost, and proactive strategies. Annual FAME utilization is optimized through linear programming, while economic uncertainty is assessed using 1,000 Monte Carlo iterations. Deterministic sensitivity analysis examines alternative NZF targets and Remedial Unit (RU) prices under fixed fuel compositions. Results indicate that IMO NZF becomes the primary driver of FAME adoption after 2030, with utilization reaching approximately 40% in the mid-2030 s and exceeding 80% by 2040. Although FAME increases fuel costs, EU ETS savings, FuelEU pooling revenues, and NZF incentives partially offset these expenditures. Sensitivity results demonstrate that uncertain NZF targets and RU prices significantly influence long-term compliance costs without altering fuel compositions. Overall, FAME offers potential as a transitional compliance and cost-optimization option, highlighting the importance of market and regulatory uncertainties in maritime decarbonization planning.
Congestion at charging stations causes uneven infrastructure utilization and restricts user mobility, potentially slowing battery electric vehicle adoption. This study examines how dynamic pricing can make users more flexible in when, where, and how long they charge. Using a survey-based experiment, we quantify the price reductions needed to induce each type of flexibility. Among consistently price-responsive respondents, average required reductions were 23.8% for charging 1 km farther away, 24.5% for shifting from daytime to nighttime, and 29.7% for accepting doubled charging duration. Responsiveness varied with battery electric vehicle charging experience, mobility patterns, and socio-demographic characteristics. By testing a broad range of price incentives in a survey-based experiment, this study complements field experiment evidence and informs the design of targeted dynamic pricing schemes that improve charging infrastructure utilization while accounting for heterogeneous user preferences.
