International Journal of Big Data Mining for Global Warming

One of the most serious challenges in the world is climate change. This study examines variations in seasonal and yearly fluctuations in extreme temperatures and precipitation in Ethiopia from 1987 to 2020 using 36 meteorological stations located in various climatic zones. The outcomes of the study demonstrated increased trends in the average annual maximum and minimum temperatures, with values of 0.094^∘C and 0.052^∘C, respectively. Despite falling trends in the summer, most stations experienced higher winter temperatures than summer. Furthermore, the analysis revealed a trend toward an increase in the number of rain stations over the summer season, while a trend toward a decrease in the amount of precipitation for a number of stations in the winter season; otherwise, large changes expected in the dega (cold), woina dega (cool), and kola (warm) climatic zones during the summer season did not occur. Precipitation activity has been near normal in most dega (cold), woina dega (cool), and kola (warm) climatic zones over the preceding 33 years. However, precipitation in the berha (hot) climatic zone was lower than average, with fluctuating levels noted throughout the year. The average annual precipitation has been decreasing at a rate of 0.146mm per year over the past 33 years, indicating that only the winter season has shown a downward (decreasing) trend, while the other three seasons, such as summer, spring, and autumn, have shown growing trends. Furthermore, Ethiopia’s average annual rainfall continues to be on a downward trend (decreasing).

A nonlinear mathematical model is proposed and analyzed to study the effect of mitigation options on the control of methane emissions in the atmosphere caused by livestock and human populations so as to reduce global warming. Livestock population is one of the main agricultural sources of greenhouse gases in the world. It is assumed that the atmospheric concentration of methane increases in the atmosphere due to cumulative density of methane formed by various processes involved in the farming of livestock populations. Various human activities are also significant contributors to methane emissions. The most notable effects of global warming around the world include the progressive heating of the Earth’s surface, oceans and atmosphere; glacier melting; and various diseases. Mitigation options are applied to control the methane emissions considerably in the atmosphere caused by livestock and human populations which in turn reduces the effects of global warming. The data from model prediction is compared with actual methane data in the atmosphere and found to be fairly close.

Depleting terrestrial deposits and rising demand for metals in this time of climate change are stimulating interest in the deep sea — the area of the ocean below 200m — with commercial mining of mineral deposits imminent. Environmental impact assessments, effective regulation and mitigation strategies are needed to limit the impacts of deep-sea mining. This is a potential catastrophe for marine biodiversity, and use of Big Data will be needed to follow mining activities as well as chart impacts on known and unknown marine species and their habitats.