Geospatial Analysis of the Global Supply Chain and Transportation Infrastructure Considering Extreme Weather, Climate, and Sustainable Energy Policies
The basis of this research is an investigation into the demand, costs, and emissions of a container freight shipping route from South America to the Port of Charleston, South Carolina. Ports and shipping routes play the most crucial role in the global supply chain, allowing people to maintain their...
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| Format: | Text |
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eGrove
2017
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| Online Access: | https://egrove.olemiss.edu/etd/1295 https://egrove.olemiss.edu/cgi/viewcontent.cgi?article=2294&context=etd |
| Summary: | The basis of this research is an investigation into the demand, costs, and emissions of a container freight shipping route from South America to the Port of Charleston, South Carolina. Ports and shipping routes play the most crucial role in the global supply chain, allowing people to maintain their standard of living. Once ashore, the delivery routes to five major metropolitan market cities were optimized for the lowest shipping costs for road and freight rail. The costs of transportation are a major factor in the ultimate price of consumer goods and thus must be minimized in the transportation process. Increasing the rail modeshare from 20% to 40% reduced the costs of transport by 25.4%. Emissions were also reduced, with a decrease of 10.29% in PM10, 9.09% in NOx, 20.28% in SOx, and 12.17% in CO2. The impact of coastal disasters on the global shipping and supply chain was then conveyed, stressing how resilient infrastructure must be implemented to harden the supply chain to natural disasters and extreme weather events such as tsunamis, hurricanes, and sea level rise. Earth’s rising temperature plays the most significant role in sea level rise. The next step in this research deals with modeling the Earth’s temperatures through autoregressive integrated moving average (ARIMA) model equations. ARIMA modeling allows for cyclical and seasonal time series data, such as climate indicators, to be modelled with accuracy where otherwise a linear trend model would not do so. The temperature on the surface of the Earth is shown to decrease by 1.02 °C (7.56%) in 2050 when compared to 2016. Based on these results, the ARIMA (12,0,24) model equation is recommended for future temperature predictions. Sea ice extents of the northern and southern hemispheres, both previously recorded time series data and projected values, were also modelled using ARIMA methodology. Analysis shows that southern hemisphere (Antarctic) sea ice extents will increase 14.0% in 2050 compared to 2016. Northern hemisphere sea ice extents (Arctic), ... |
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