(untitled) (Global Journal of Human-Social Science, 2024)
Kerbside collection of waste is not often included as part of carbon footprint analysis in view that it constitutes about 5e percent of the carbon emissions generated by the waste collection and treatment systems However it also represents the most expensive functional element in the entire waste management process reaching as high as 75 percent of all costs in the total municipal solid waste MSW management system Most costs relate to fuel together with labour costs Fuel consumption results in various pollutants predominantly carbon dioxide nitrogen oxides and sulfur dioxide which are of major concern due to their contribution to global warming and acid rain In Malta transport emissions generated from the MSW collection system reach 14 percent of total emissions This is significantly higher than the European average which generally reaches 5 percent During the time the study was carried out the local councils municipalities were left to their own devices to sketch a collection route with the result that truck drivers often outline a route simply on their experience Therefore room for improvement is clearly present and it is necessary to find an optimal solution to reduce fuel consumption and minimize emissions This research uses Geographic Information Systems GIS through the Arc GIS Network Analyst application to optimize routes by enhancing the efficiency of waste collection and transportation in the cities of Mellie a and Attard Malta The model that is created is based on data collection involving the Global Positioning System tracking including bin position landfill and collection route as variables Key performance indicators of the existing practice are estimated Following this potential optimal scenarios were developed and compared to the existing collection routes Results indicate that the proposed scenarios have direct positive impacts on vehicle operating times with operational cost savings and reduced carbon dioxide nitrogen oxide and particle emissions