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The massive increase in disposable plastic globally can be addressed through effective recovery methods, and one of these methods is pyrolysis. R software may be used to statistically model the composition and yield of pyrolysis products, such as oil, gas, and waxes to deduce an effective pyrolysis mechanism. To date, no research reports have been documented employing the Arrhenius equation in R software to statistically forecast the kinetic rate constants for the pyrolysis of high-density plastics. We used the Arrhenius equation in R software to assume two series of activation energies (Ea) and pre-exponential factors (Ao) to statistically predict the rate constants at different temperatures to explore their impact on the final pyrolysis products. In line with this, MATLAB (R2020a) was used to predict the pyrolysis products of plastic in the temperature range of 370–410 °C. The value of the rate constant increased with the temperature by expediting the pyrolysis reaction due to the reduced frequency factor. In both assumed series of Ea and Ao, a significantly larger quantity of oil (99%) was predicted; however, the number of byproducts increased in the first series analysis compared to the second series analysis. It was revealed that an appropriate combination of Ea, Ao, and the predicted rate constants could significantly enhance the efficiency of the pyrolysis process. The major oil recovery in the first assumed series occurred at 390 °C to 400 °C, whereas the second assumed series of Ea and Ao occurred at 380 °C to 390 °C. In the second series at 390 °C to 400 °C, the predicted kinetic rate constants behaved aggressively after 120 min of the pyrolysis process. The second assumed series and anticipated rate constants at 380 °C to 390 °C can be applied commercially to improve oil production while saving energy and heat.

The energy received by solar collectors for power generation is limited to various conditions. The average data on solar irradiation are normally used to determine the potential of solar energy at any location. However, the variation of solar energy due to seasonal differences could affect the actual performance of the collectors, consequently leading to poorly justified system installations, which are high in cost. In this work, the characteristics of solar energy radiation in Kuwait were studied by measuring irradiance and comparing the data of selected time periods in two extreme seasons. A pyranometer, mounted two meters above the ground on a tubular beam in a shade-free area at a solar energy laboratory in Kuwait was used to measure irradiance on three consecutive days in summer and winter. The radiation data were recorded at five-minute intervals in each season for comparison. It was found that the average irradiance energy in the winter was up to 61% less than in the summer. In addition, the study revealed that the day-to-day variation of irradiance in winter (31%) was approximately 6.5 times higher than in the summer (4.8%). Clearly, the operation of solar power generation systems in the area during winter would face significant day-to-day fluctuations. As a result, this would necessitate frequent operation of backup power systems in order to meet the electrical power load demand.