Sustainability Evaluation of Cold In-Place Recycling and Hot Mix Asphalt Pavements: A Case of Qassim, Saudi Arabia

The construction of conventional hot mix asphalt (HMA) pavements results in a number of economic and environmental issues, such as the cost of new overlays and associated impacts on natural resources. Although the cold recycling with an emulsified asphalt-recycling agent holds certain benefits over the HMA, its implementation on different road types, ranging from farm-to-market roads to expressways, is yet contentious due to the need for sophisticated equipment and trained workforce. The present research developed a methodology to evaluate all the three dimensions of sustainability, including economic (construction cost), environmental (natural resource depletion), and social (need for advanced equipment and skilled labor) of various scenarios of RAP and conventional asphalt pavements. The present study evaluated an equivalent thickness of the Cold In-place Recycling (CIR) pavement, which behaves similar to HMA pavement under the influence of different traffic loads. Fifty CIR and HMA scenarios for different traffic volumes and pavement layers thicknesses were developed. Finally, the sustainability of all the scenarios was evaluated for traffic designation in Saudi Arabia using fuzzy-based multicriteria analysis. Ranking of scenarios found CIR as a more sustainable overlay option for the feeders, collectors, main urban streets, expressways, and heavily trafficked highways in industrial areas where ESALs (Equivalent Single Axle Loads) range between 2,000,000 and >31,000,000. Considering the limited availability of advanced equipment and skilled labor for CIR pavements, HMA was found be a more sustainable option for farm-to-market roads with the “very light” traffic class. The methodology will help the pavement managers in decision making regarding the selection of sustainable pavement technologies for different road types in Saudi Arabia and the rest of the world.

Effects of the COVID-19 Pandemic on the Air Quality of the Metropolitan Region of São Paulo: Analysis Based on Satellite Data, Monitoring Stations and Records of Annual Average Daily Traffic Volumes on the Main Access Roads to the City

This paper presents an analysis of the effects of the COVID-19 pandemic on the air quality of the Metropolitan Region of São Paulo (MRSP). The effects of social distancing are still recent in the society; however, it was possible to observe patterns of environmental changes in places that had adhered transportation measures to combat the spread of the coronavirus. Thus, from the analysis of the traffic volumes made on some of the main access highways to the MRSP, as well as the monitoring of the levels of fine particulate matter (PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2), directly linked to atmospheric emissions from motor vehicles–which make up about 95% of air polluting agents in the region in different locations–we showed relationships between the improvement in air quality and the decrease in vehicles that access the MRSP. To improve the data analysis, therefore, the isolation index parameter was evaluated to provide daily information on the percentage of citizens in each municipality of the state that was effectively practicing social distancing. The intersection of these groups of data determined that the COVID-19 pandemic reduced the volume of vehicles on the highways by up to 50% of what it was in 2019, with the subsequent recovery of the traffic volume, even surpassing the values from the baseline year. Thus, the isolation index showed a decline of up to 20% between its implementation in March 2020 and December 2020. These data and the way they varied during 2020 allowed to observe an improvement of up to 50% in analyzed periods of the pollutants PM2.5, CO and NO2 in the MRSP. The main contribution of this study, alongside the synergistic use of data from different sources, was to perform traffic flow analysis separately for light and heavy duty vehicles (LDVs and HDVs). The relationships between traffic volume patterns and COVID-19 pollution were analyzed based on time series.

Efficiency Assessment of a Signalized Roundabout and a Traffic Intersection in Baghdad City

In Baghdad city, Iraq, the traffic volumes have rapidly grown during the last 15 years. Road networks need to reevaluate and decide if they are operating properly or not regarding the increase in the number of vehicles. Al-Jadriyah intersection (a four-leg signalized intersection) and Kamal Junblat Square (a multi-lane roundabout), which are two important intersections in Baghdad city with high traffic volumes, were selected to be reevaluated by the SIDRA package in this research. Traffic volume and vehicle movement data were abstracted from videotapes by the Smart Traffic Analyzer (STA) Software. The performance measures include delay and LOS. The analysis results by SIDRA Intersection 8.0.1 show that the performance of the roundabout is better than the signalized intersection but experiences high delay, and low LOS. Therefore, alternatives are proposed to improve the performance for current and future traffic volumes with low-medium delays.

Assessment of sustainability of the Lviv city transport system according to the indicator of accessibility

Transport accessibility of the territory determines the possibility of getting a certain area using a certain transport mode of the existing transport network. The paper describes the concept of accessibility of the territory as a factor of sustainability of the urban transport system and methods of its assessment for urban conditions. It is proposed to use the indicator of the number of non-stop public transport routes between transport zones as a criterion for the "cost" of travel. Non-stop travel increases the comfort of public transport and reduces the financial costs of the passenger. The route network of the city of Lviv and interconnections of transport zones by public transport routes (bus, tram, and trolleybus) are analyzed. Modelling of passenger traffic volumes and their distribution by modes (private transport, public transport, and pedestrian traffic) was done in the PTV Visum software based on the matrix of a duration of movement and the matrix of the number of non-stop routes. It was found that at commensurate distances between transport zones, the number of non-stop routes increases the share of public transport users. The relationship between the number of non-stop routes and the share of public transport users is described by the logarithmic dependence. Comparing the simulated passenger flows on the public transport routes with the results of field researches, it was found that taking into account the number of non-stop routes between transport zones during the simulation allows increasing the accuracy of the results. Further research may focus on analyzing the impact of other factors that characterize the accessibility of the territory on the distribution of transport users between modes, and on the development of recommendations to the responsible city authorities to improve the city's passenger route network.

Resilience of Railway Transport to Four Types of Natural Hazards: An Analysis of Daily Train Volumes

A crucial step in measuring the resilience of railway infrastructure is to quantify the extent of its vulnerability to natural hazards. In this paper, we analyze the vulnerability of the German railway network to four types of natural hazards that regularly cause disruptions in German rail operations: floods, mass movements, slope fires, and tree falls. Using daily train traffic data matched with various data on disruptive events, we quantify the extent to which these four types of natural hazard reduce daily train traffic volumes. With a negative binomial count data regression, we find evidence that the track segments of the German railway network are most vulnerable to floods, followed by mass movements and tree-fall events. On average, floods reduce traffic on track segments by 19% of the average daily train traffic, mass movements by 16%, and tree fall by 4%. Moreover, when more than one type of natural hazard affects the track segment on the same day, train traffic on that segment falls by 34% of the average train traffic. Slope fires have an ambiguous and nonrobust effect on train traffic due to the reverse causality due to its triggering factors. This is the first study that attempts to rank different natural hazards according to their impact on railway traffic. The results have implications for the selection of resilience strategy and can help prioritize policy measures.

On Site Improvement of Fines-Rich Unbound Granular Materials with Hydrophobic Polymer and Lime

Many roads that were initially designed for relatively low traffic volumes need re-surfacing or partial replacement of the unbound granular material to satisfy current traffic demand. Significant research efforts based on laboratory studies have been seen in the literature to characterize the suitability of virgin materials, which is relatively expensive and unsustainable. Therefore, the object of this study is the in situ recycling of existing materials in two road sections by improving their properties with a suitable additive. A hydrophobic synthetic polymer was chosen for two trials due to the high plasticity of fines of the in situ materials and a high chance of water intrusion in the low-lying plains in Adelaide. The extensive laboratory characterization shows that hydrophobicity is imparted in capillary rise tests, improved drainage in permeability tests, and greater matric suction at the same moisture content. Furthermore, the unconfined compressive strength was increased. The repeated loading triaxial testing showed higher stiffness and lowered permanent strain to withstand higher traffic volume. In general, in situ recycling is adaptable and considered to be cheaper and sustainable. The estimated current costs and carbon footprints are presented for re-construction and in situ recycling with dry powder polymer, or solely with lime, to help construction planning.

THE SAIMAA CANAL IN THE INLAND WATER CARGO TRANSPORTATION SYSTEM

The article deals with the research of the Saimaa Canal significance in the Finnish transport sphere. The analysis of the canal characteristics and features, which are es-sential for shipping, as well as the Saimaa Canal traffic volumes, their commodity struc-ture, the Saimaa Canal ship calls and cargo traffic pattern of change are given. The cer-tain prospects for increasing the traffic on the Saimaa Lakes and especially on the ca-nal is considered.

Transferability of a Machine Learning-Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study

This paper focuses on the problem of model transferability for machine learning models used to estimate hourly traffic volumes. The presented findings enable not only an increase in the accuracy of existing models but also, simultaneously, reduce the cost of data needed for training the models—making statewide traffic volume estimation more economically feasible. Previous research indicates that machine learning volume estimation models that leverage GPS probe data can provide transportation agencies with accurate estimates of hourly traffic volumes—which are fundamental for both operational and planning purposes—and do so with a higher level of accuracy than the prevailing profiling method. However, this approach requires a large dataset for model calibration (i.e., input and continuous count station data), which involves significant monetary investment and data-processing effort. This paper proposes solutions, which allow the model to be prepared using a much smaller dataset, given that a previously collected dataset, which may be gathered in a different place and time period, exists. Based on a broad selection of experiments, the results indicate that the proposed approach is capable of achieving similar model performance while collecting data for a 5 times shorter time period and utilizing 1/4 of the number of continuous count stations. These findings will help reduce the cost of preparing and maintaining the traffic volume models and render the traffic volume estimations more financially appealing.

Elemental Composition of PM2.5 and PM10 and Health Risks Assessment in the Industrial Districts of Chelyabinsk, South Ural Region, Russia

Air pollution impacts all populations globally, indiscriminately and has site-specific variation and characteristics. Airborne particulate matter (PM) levels were monitored in a typical industrial Russian city, Chelyabinsk in three destinations, one characterized by high traffic volumes and two by industrial zone emissions. The mass concentration and trace metal content of PM2.5 and PM10 were obtained from samples collected during four distinct seasons of 2020. The mean 24-h PM10 ranged between 6 and 64 μg/m3. 24-h PM2.5 levels were reported from 5 to 56 μg/m3. About half of the 24-h PM10 and most of the PM2.5 values in Chelyabinsk were higher than the WHO recommendations. The mean PM2.5/PM10 ratio was measured at 0.85, indicative of anthropogenic input. To evaluate the Al, Fe, As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn concentration in PM2.5 and PM10, inductively coupled plasma mass spectrometry (ICP-MS) was used. Fe (337–732 ng/m3) was the most abundant component in PM2.5 and PM10 samples while Zn (77–206 ng/m3), Mn (10–96 ng/m3), and Pb (11–41 ng/m3) had the highest concentrations among trace elements. Total non-carcinogenic risks for children were found higher than 1, indicating possible health hazards. This study also presents that the carcinogenic risk for As, Cr, Co, Cd, Ni, and Pb were observed higher than the acceptable limit (1 × 10−6).

Edge Computing in IoT: A 6G Perspective

Edge computing is one of the key driving forces to enable Beyond 5G (B5G) and 6G networks. Due to the unprecedented increase in traffic volumes and computation demands of future networks, Multi-access Edge Computing (MEC) is considered as a promising solution to provide cloud-computing capabilities within the radio access network (RAN) closer to the end users. There has been a huge amount of research on MEC and its potential applications; however, very little has been said about the key factors of MEC deployment to meet the diverse demands of future applications. In this article, we present key considerations for edge deployments in B5G/6G networks including edge architecture, server location and capacity, user density, security etc. We further provide state-of-the-art edge-centric services in future B5G/6G networks. Lastly, we present some interesting insights and open research problems in edge computing for 6G networks.