Travel times on inland waterways : historic statistical calculations between selected locks and river confluences using Automatic Identification System (AIS) data from calendar year 2021
In the context of multimodal-freight modeling efforts, the US Army Corps of Engineers (USACE), Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory (CHL), entered into an inter-agency agreement with the Department of Transportation (USDOT), Bureau of Transportation Statistics (BTS), to produce travel-time statistics for select portions of the US inland waterway transportation system. Statistics include the median, interquartile range average, and 10th–90th percentile averages between origin and destination (OD) sets selected based on vessel traffic activity, especially lock and dam locations, which are natural stopping points. Travel-time statistics are derived from position reports broadcast via Automatic Identification System (AIS) transceivers for vessel transits that occurred in 2021. This technical report summarizes the methodology and findings.
Bottom-up ship emission inventories derived from Automatic Identification System (AIS) data are normally reported on kilometre-scale grids, which merge port waters that perform very different functions. Working with an AIS-based STEAM inventory for the Yangtze River Delta (YRD), we ask a question that gridded inventories rarely separate: are the cells where ships accumulate time the same cells where they emit? To answer it, we define the Static–Dynamic Ratio (SDR), the ratio of hotelling (auxiliary-engine) to propulsion (main-engine) emissions within a cell, and use it to classify YRD waters without recourse to external port charts. Hotelling-dominated cells occupy 17.7% of the sea area and accumulate 59.3% of all ship-hours, a ship-hour density seven times that of transit-dominated fairways, yet they carry only 22.4% of NOx. A vessel at anchor emits about one-eighth as much NOx per hour as one under way, and the two effects nearly cancel. The cancellation is species dependent: low-load correction factors are steeper for sulfur and particulate species than for NOx, so hotelling zones reach relative SO2 and PM2.5 densities of 1.21 and 1.09 against 0.89 for NOx. Coarsening the same activity field from 100 m to 1 km drops the share held by the busiest 1% of cells from 70% to 50%, showing how kilometre grids manufacture apparent continuity along shipping lanes. Activity hotspots are therefore not emission hotspots, and anchorage-targeted measures such as shore power are best justified by particulate and sulfur exposure near populated coasts rather than by their share of the regional NOx burden.
Chen Liu, Rongchang Chen, Shuting Sun et al.· Atmosphere· 0 citations
This study examines the temporal and spatial patterns of Toronto Transit Commission (TTC) subway delays in Toronto using the TTC Subway Delay Data. The dataset contains 28,191 delay records from January 1, 2025, to January 31, 2026, and the 2025 records are selected for analysis. Descriptive statistics and data visualization are used to examine hourly and station-level delay patterns. A random forest classification model is developed to predict whether at least one delay incident will be recorded during a specific date-hour period at Union Station. The results show that TTC subway delays are unevenly distributed across time and stations. Delay incidents are more frequent around 22:00, while several major stations, including the Kennedy Bloor-Danforth Line (BD), Bloor, Finch, Kipling, and Union Station, record relatively high numbers of delay incidents. The classification model achieves relatively high recall but low precision, indicating that it identifies many date-hour periods containing recorded delay incidents.
Yifei Liu· Applied and Computational En...· 0 citations
Flooding along the Bontang River in Gunung Telihan Village, Bontang City, recurs almost annually, yet its causes had not been diagnosed mechanistically. This study applied one dimensional steady-flow HEC-RAS 4.1 modeling to a 1,936 m reach, using primary topographic data and design discharges (Q2, Q10, Q20) from the Nakayasu Synthetic Unit Hydrograph. Unlike prior single mechanism studies, the analysis resolved four co occurring flood mechanisms: bank-asymmetry overflow, right bank levee overflow, undersized sluice-gate backwater, and a downstream constriction. Although nominal channel capacity (13.83 m3/s) marginally exceeded Q2 (11.88 m3/s), the low right bank reduced the effective overflow threshold below Q2. A 95% confidence interval on design discharge, computed using Kite's asymptotic method, indicated the downstream constriction could approach overflow at the upper bound of Q10 uncertainty. An independent tidal sensitivity check showed the tidal range effect at the confluence (2.2 m) exceeded the sluice-gate backwater step alone (0.42-0.68 m). A planned condition simulation combining retention ponds, levee reinforcement, and gate augmentation achieved safe status at all critical points, indicating site differentiated intervention is a promising, land feasible direction pending detailed design verification.
Viva Oktaviani, Heri Purnomo· ZERO Jurnal Sains Matematika...· 0 citations
Rapid urban motorization in Makassar has intensified roadside exposure to traffic-related pollutants. This study empirically evaluates the direct statistical relationship between traffic volume and roadside nitrogen dioxide (NO2) concentration along a major arterial corridor. Field measurements were conducted during three time periods (morning, midday, and afternoon) on one representative weekday and one weekend day. Traffic volume was converted to Passenger Car Units (PCU), and NO2 concentration was measured using the Griess-Saltzman method in accordance with national standards. Pearson correlation and simple linear regression were applied to quantify the emission–concentration relationships at the microscale level. The results indicated a strong positive correlation between traffic volume and NO2 concentration (r = 0.874, p < 0.05), with traffic density explaining 76.3% of the variability in concentration (R2 = 0.763). Despite limited temporal coverage, the findings demonstrate that traffic congestion is a dominant determinant of short-term roadside NO2 accumulation. This study provides localized empirical evidence supporting traffic-based emission control strategies in emerging urban environments.
Expressways are designed to facilitate uninterrupted traffic flow; however, localized roadside features such as bus laybys disrupt vehicle dynamics and reduce operational capacity. While classical speed–density models provide theoretical foundations for freeway analysis, localized disturbances are frequently omitted from conventional modeling. This study evaluates the speed–density relationship of passenger cars on a basic expressway segment adjacent to a bus layby along the Federal Highway (KM 17) in Selangor, Malaysia. Traffic data were collected across peak and off-peak periods using elevated video recordings and analyzed via Tracker motion-analysis software across 36 five-minute intervals. Comparative evaluation against classical single-regime models demonstrated that the linear Greenshields model ($V_s = 116.97 - 1.381k$) provided the most robust fit, explaining 75.05% of the variation in passenger car speed ($R^2 = 75.05\%$, $F = 102.27$, $p < 0.001$). The empirical findings indicate that each 10-unit increase in density ($pcu/km$) induces an approximate 14 $km/h$ reduction in speed, largely driven by lane-changing turbulence and deceleration near the layby weave zone. These results underscore the need for infrastructure authorities to incorporate localized disturbance factors into expressway capacity planning and offer actionable insights for optimizing bus layby geometry and setback distances to preserve highway efficiency.
Ifham Fathi Sayuti, T. Besar, Noorazlan Hasnim et al.· International journal of res...· 0 citations
Fuel consumption at tropical airports in developing regions remains poorly documented, creating a significant empirical gap in both academic literature and operational guidance. This paper presents a comprehensive assessment and analysis of aircraft fuel consumption at Maya-Maya International Airport (FCBB), Republic of the Congo, using four years of operational data (2021–2024) covering 22,968 flight movements. Fuel consumption is estimated using the ICAO Carbon Emissions Calculator (ICEC v13.1), and a distance-based allocation approach is introduced to decompose the total fuel consumption into airborne and ground operation components. A reproducible engineering methodology is developed, combining the ICAO calculator with a parametric ground fuel allocation and log-linear regression analysis. Over the study period, the total fuel consumption reached 183,010 tonnes, generating 578,313 tonnes of CO2. Ground operations account for approximately 7.0% of the total fuel burn (12,780 tonnes). Delay analysis reveals average delays of 19.5 min per flight with a strongly right-skewed distribution — median nine min against a maximum of 521 min — indicating that extreme events disproportionately drive total fuel burn. Regression analysis identifies flight distance, aircraft generation, and operational delays (approximately 15 kg of additional fuel per min of delay) as the primary drivers of fuel consumption. A three-phase strategic framework combining operational improvements, fleet modernization, and integrated decision-support systems projects fuel savings of 15–23% under realistic implementation scenarios. The methodological framework is transparent, replicable, and directly transferable to other data-constrained tropical airports in Sub-Saharan Africa and beyond.
Manasse Malame Kaboulou, Bienvenu Ondami, Henri Joel Ondze et al.· Engineering, Technology &...· 0 citations
