Despite the measures put in place in different countries, road traffic fatalities are still considered one of the leading causes of death worldwide. Thus, the reduction of traffic fatalities or accidents is one of the contributing factors to attaining sustainability goals. Different factors such as the geometric structure of the road, a non-signalized road network, the mechanical failure of vehicles, inexperienced drivers, a lack of communication skills, distraction and the visual or cognitive impairment of road users have led to this increase in traffic accidents. These factors can be categorized under four headings that are: human, road, vehicle factors and environmental road conditions. The advent of machine learning algorithms is of great importance in analysing the data, extracting hidden patterns, predicting the severity level of accidents and summarizing the information in a useful format. In this study, three machine learning algorithms for classification, such as Decision Tree, LightGBM and XGBoost, were used to model the accuracy of road traffic accidents in the UK for the year 2020 using their default and hyper-tuning parameters. The results show that the high performance of the Decision Tree algorithm with default parameters can predict traffic accident severity and provide reference to the critical variables that need to be monitored to reduce accidents on the roads. This study suggests that preventative strategies such as regular vehicle technical inspection, traffic policy strengthening and the redesign of vehicle protective equipment be implemented to reduce the severity of road accidents caused by vehicle characteristics.

Background: Pedestrian infrastructure is pivotal for advancing the movement of nonmotorized road users and plays a transformative role in transitioning toward sustainable transportation, especially in rural territories influenced by urban dynamics and interconnected by daily commuter flows. Both walking and cycling stand out as paramount sustainable transport means, offering substantial health and environmental benefits, including reduced noise and air pollution. Multiple factors, such as convenience, safety, accessibility, service cost, flexibility, and the quality of pedestrian pathways, shape individuals' propensity to walk. Notably, in peri-urban contexts, the cost of service becomes a significant determinant, as a notable proportion of the population earns minimal wages or faces unemployment. Objective: This study sought to examine the current state of pedestrian walkways within Pietermaritzburg and surrounding areas, through which the accessibility, availability, and quality of these facilities were assessed. The study has suggested possible solutions to address the challenges faced by pedestrians. Methods: By conducting semi-structured interviews and leveraging ArcGIS mapping utilities, this research has delineated the existing scenario and offered an initial redesign tailored to pedestrian requirements. Results: The data have starkly revealed pervasive inadequacies in the existing pedestrian infrastructure. The functionality and safety of current amenities have been manifestly undermined by these shortcomings. The continuing use of these dilapidated facilities may pose alarming threats not only to pedestrians, but also to other road users.

Road traffic accidents are associated with different factors, such as nonsignalised road networks, inexperienced drivers, a lack of communication skills, distraction, and the visual or cognitive impairment of road users, which have led to this increase in traffic accidents. Understanding these factors in alignment with road user communication skills can provide solutions that can reduce traffic fatalities. Road users’ communication is predominantly formal in nature; informal means of communication also exist but are not given proper attention during the driving training and licence testing processes. Therefore, this study investigated the communication skills between drivers as a factor contributing to traffic accidents in South African cities. Consequently, 16 traffic scenarios of communication between drivers were simulated using PTV Vissim 2022 and Blender 3.0 software, and a semistructured interview questionnaire was used to collect data from South African road users. The questionnaire was further used to evaluate the confidence level of road users concerning informal communication. The data were analysed via regression analysis to establish the relationship between traffic accidents and miscommunication between drivers. The information gathered and analysed from this study helps us to understand the informal communication types between drivers and establish where communication loss exists, which could potentially lead to a traffic accident. The results also show that the misinterpretation of communication signals can present the possibility of a traffic safety risk.

The global production of electronic waste (e-waste) has increased due to the quick turnover of electronic devices, creating urgent problems for resource management and environmental sustainability. As a result, e-waste-derived materials (EWDMs) are being explored in pavement engineering research as sustainable substitutes in line with Sustainable Development Goals (SDGs), specifically SDG 9 (Industry, Innovation, and Infrastructure), 11 (Sustainable Cities and Communities), 12 (Responsible Consumption and Production), and 13 (Climate Action). Therefore, to assess global research production and the effectiveness of EWDMs in asphalt applications, this review combines scientometric mapping and systematic evidence synthesis. A total of 276 relevant publications were identified via a thorough search of Web of Science, Scopus, and ScienceDirect (2010–2025). These were examined via coauthorship structures, keyword networks, and contributions at the national level. The review revealed that China, India, and the United States are prominent research hubs. Additionally, experimental studies have shown that EWDMs, such as printed circuit board powder, fluorescent lamp waste glass, high-impact polystyrene, and acrylonitrile–butadiene–styrene, improve the fatigue life, Marshall stability, rutting resistance (up to 35%), and stiffness (up to 28%). However, issues with long-term field durability, microplastic release, heavy metal leaching, and chemical compatibility still exist. These restrictions highlight the necessity for standardised toxicity testing, harmonised mixed-design frameworks, and performance standards unique to EWDMs. Overall, the review shows that e-waste valorisation can lower carbon emissions, landfill build-up, and virgin material extraction, highlighting its potential in the circular pavement industry and promoting sustainable paving practices in accordance with SDGs 9, 11, 12, and 13. This review suggests that further studies on large-scale field trials, life cycles, and technoeconomic assessments are needed to guarantee the safe, long-lasting integration of EWDMs in pavements. It also advocates for coordinated research, supportive policies, and standardised methods.

Carbon footprint assessment is important to combat global warming and promote sustainability. Globally, organizations committed to biodiversity conservation are essential for maintaining ecosystems and the people who inhabit them. Nonetheless, these organizations produce a carbon footprint due to their operating operations. Hence, this study aimed to assess the specific carbon footprint of the Ezemvelo KZN Wildlife (EKZNW) to improve its understanding of its environmental implications and encourage sustainable behaviors within its particular missions. Using the greenhouse gas protocol corporate accounting and reporting standard as a guide, the study methodology examines greenhouse gas emissions from direct (Scope 1) and indirect (Scopes 2 and 3) sources related to Ezemvelo wildlife activities over five years (2014/2015--2018/2019). The results show that 34,016.62 tons of carbon dioxide equivalent (tCO2e) are emitted on average each year. The majority of these emissions are caused by Scope 2 electricity consumption, which accounts for 23,475.82 tCO2e, and Scope 1 emissions, which account for 7,826.20 tCO2e. Furthermore, there was a noticeable difference in emissions between the reserves, with the Imfolozi Game Reserve having the highest emissions. The findings of this study direct EKZNW toward ecologically conscious behaviors by acting as a catalyst for educated decision-making. The insight gained paves the way for proactive steps to lower carbon emissions, coordinating conservation efforts with more general goals of sustainability and climate resilience.