The transport sector is the leading source of growing greenhouse gas (GHG) emissions globally. To consider environmental degradation aspects due to transport, electric vehicles (EVs) have the prospect to lead road transport to electric mobility from conventional petroleum vehicles. Despite various eco-friendly benefits, the EV market penetration ratio is very low, especially in developing countries. The primary reason for low penetration is consumer limited motivation and knowledge about the EVs features. This paper uses a unified theory of acceptance and technology (UTAUT) model to assess consumer motivation and environmental knowledge towards EVs. This research used convenience random sampling to collect data and analyzed the results using the Partial Least Squares (PLS) method on the example of 199 respondents from Malaysia. The study results revealed that factors identified in the motivational context significantly influence consumer intentions to purchase EVs. Perceived environmental knowledge and technophilia have been included in UTAUT from a motivational perspective. Furthermore, a significant relationship between effort expectancy, social influence, technophilia, perceived environmental knowledge, and purchase intention towards electric vehicles has been observed, without performance expectancy. The study findings serve to inform policymakers and automakers to formulate effective marketing strategies to enhance consumer motivation, knowledge, and value creation for EVs in a sustainable era. Ultimately, the policies will help to encourage consumers to buy eco-friendly vehicles that will help reduce transport carbon emissions and attain sustainable development goals (SDGs).

The existing form of self-compacting concrete (SCC) comprises of a large amount of powdered and fine materials. In this study, a part of the cementitious material was replaced with constant high-volume fly ash, and a portion of fine aggregates was substituted by crumb rubber (CR). Besides that, silica fume (SF) was added, with the hope that by implementing a new type of nanomaterial, the loss in mechanical strength due to previous modifications such as rubberization and replacement will be prevented. Two variables were found to influence the constituent/component in the mix design: SF and CR. The proportion of SF varies from 0% to 10%, while that of CR from 0% to 30% by volume of the total river sand, where 55% of cement was replaced by the fly ash. A total of 13 rubberized SCC samples with CR and SF as controlling variables were made, and their design mix was produced by a Design of Experiment (DOE) under the Response Surface Methodology (RSM). The results reveal a slight increase in the mechanical properties with the addition of SF. The theoretical mathematical models and equation for each different mechanical strength were also developed after incorporating the experimental results into the software.

In the construction and maintenance of asphalt pavement, reclaimed asphalt pavement (RAP) is being widely used as a cheaper alternative to the conventional hot mix asphalt (HMA). HMA incorporated with a high RAP content (e.g., 40%), which is the most commonly used, may have prominent adverse effects on life cycle, performance properties, and related costs. Thus, before utilizing RAP, it is essential to investigate whether it is still economical to use under the local climate by taking into consideration the life cycle performance. Therefore, for this paper, a case study was conducted using 20% RAP, assessed in terms of materials related to cost analysis. The results of the analysis showed that, from the total life cycle costing measurement, a total of 14% cost reduction was reported using RAP as compared to conventional materials. Moreover, the two materials (conventional HMA and RAP) are manufactured in different types of manufacturing plants. Thus, in analyzing the cost difference between the two chosen manufacturing plants for virgin materials and RAP, a total of 57% cost reduction was observed for a RAP manufacturing plant. Besides this, no cost difference was observed in the rest of the phases, such as manpower, materials transportation, and construction activities, as the same procedures and types of machinery are used. Furthermore, assessing the carbon dioxide impact and cost, the transportation and machinery emissions were considered, while the plant’s operation emission was omitted due to the unavailability of the data.

The hybrid type of pavement called semi-flexible or grouted macadam has gained popularity over the last few decades in various countries, as it provides significant advantages over both rigid and conventional flexible pavements. The semi-flexible pavement surface consists of an open-graded asphalt mixture with high percentage voids into which flowable cementitious slurry is allowed to penetrate due to gravitational effect. Several researchers have conducted laboratory, as well as field, experiments on evaluating the performance of semi-flexible layers using different compositions of cementitious grouts. The composition of grouts (i.e., water/cement ratio, superplasticizer, polymers, admixtures, and other supplementary materials) has a significant effect on the performance of grouts and semi-flexible mixtures. A comprehensive review of cementitious grouts and their effect on the performance of semi-flexible layers are presented and summarized in this review study. The effect of byproducts and other admixtures/additives on the mechanical properties of grouts are also discussed. Finally, recommendations on the composition of cementitious grouts have been suggested.

The water level in a river defines the nature of flow and is fundamental to flood analysis. Extreme fluctuation in water levels in rivers, such as floods and droughts, are catastrophic in every manner; therefore, forecasting at an early stage would prevent possible disasters and relief efforts could be set up on time. This study aims to digitally model the water level in the Kabul River to prevent and alleviate the effects of any change in water level in this river downstream. This study used a machine learning tool known as the automatic autoregressive integrated moving average for statistical methodological analysis for forecasting the river flow. Based on the hydrological data collected from the water level of Kabul River in Swat, the water levels from 2011–2030 were forecasted, which were based on the lowest value of Akaike Information Criterion as 9.216. It was concluded that the water flow started to increase from the year 2011 till it reached its peak value in the year 2019–2020, and then the water level will maintain its maximum level to 250 cumecs and minimum level to 10 cumecs till 2030. The need for this research is justified as it could prove helpful in establishing guidelines for hydrological designers, the planning and management of water, hydropower engineering projects, as an indicator for weather prediction, and for the people who are greatly dependent on the Kabul River for their survival.