RESUMEN
The global increase in the plastic waste has resulted in significant pollution increase which causes significant damage to the environment. There is an urgent need for waste management practices such as recycling to ensure sustainable development and decreasing the impact of plastic waste on the environment. The production of new materials such as graphene are associated with high cost, and there have been research efforts to develop cost effective alternative sources of graphite. considerable research has been carried out on investigating the application of homo polypropylene in asphalt construction. successful applications of this will ensure recycling and reduce waste footprint of plastic. The paper presents a proposed method of synthesising graphene from plastic waste and talc at 80 %, and 20 % of that after many experiments. Graphene was monitored at (002). (100). (004) peaks at 2 θ = 26.8°, 42°, with 53 successive physical tests conducted to determine the quality of the graphene produced. The experiments carried out resulted in a successful production of a 98 % pure material. The synthesised graphene was then combined with asphalt using different ratios of weight: 2 %, 6 %, 8 %, and 10 % to test the physical properties of the combination. The results were compared with no graphene usage, the findings validated the findings of similar studies which demonstrate at 6 % ration combination with graphene the asphalt provides better results than without graphene. Also, testing at alternative forces of 6.5 psi and 13 psi at temperatures of 25, 40 and 60, the results showed a noticeable improvement. All tests showed better results in creep and tensile strength. It is concluded that there is a proofed concept to follow this approach to recycle waste plastic in ample ways to reduce the footprint of waste.
RESUMEN
Despite recent measures on accident prevention, road collisions, mainly on London's "A" roads, persist as accident sources, endangering vulnerable users in particular. Analysing evidence from London's A-Roads unveils issues concerns and trends. This study utilises extensive data to target factors magnifying accidents: speed, traffic, vulnerable interactions. Stats 19 and transport data including volumes, types, speeds, and congestion parameters are all analysed alongside the collision data. The descriptive statistics have been employed to understand nature of data in the first instance. This has supported the process to cleanse the data outliers or periods where were subjected to incidents and interventions. Predictive model development is conducted to analyse and forecast accident frequency using ARIMA and SARIMAX models forecasted accident rates and interventions. ARIMA yielded higher accuracy. Method of analysis resulted in a statistically reliable formulation of the main factors, enabling use of this method for similar cities across the world. Formulated analysis revealed key contributors as population density, weather, and time of the day. The analysis of data supported identification of strategies emerging as infrastructure improvements, traffic control measures and severity and vulnerable users affected in particular. The analysis reveals distinct exhibits of causation, leading to focused recommendations on infrastructure enhancements, traffic control measures, and the impact on severity and vulnerable users, deviating from prior research findings. Insights aid safer London roads, have global predictive and mitigation value.
