Integrated Solid Waste Management For Environmental Risks Reduction In Dar Es Salaam,tanzania

Solid waste management(SWM)is an increasing problem mainly because of the rising waste generation,and a declining supply of adequate waste disposal facilities.This resulting in adverse environmental and health-related impacts.To deal with this problem,SWM methods aimed at waste reduction and diversion through increased recycling,recovery,and re-use by changes in consumer behavior are of particular importance.This research proposes the adoption of an integrated solid waste management(ISWM)system/plan for sustainable management of solid waste(SW)to reduce environmental risks from SW-induced pollution in Dar es Salaam,Tanzania.To do this,it first investigated the actual SWM situation in the area by assessing the present management system where the gaps were identified.It used the primary data to develop the baseline information which was saved as data input for the application of the multi-layer perceptron artificial neuron network(MLP-ANN)models to predict the future of waste generation rates(WGRs)which is an important part of ISWM.Then,it assessed the environmental risk of Dar es Salaam SW which currently has become an area of major concern.In this task,the study employed the Driving forces-Pressure-State-Impact-Response(DPSIR)model to establish an environmental risk indicator system and the multi-criteria decision analysis based on the analytical hierarchy process(MCD-AHP)methods to calculate and analyze risk values,based on the actual situation of SW in Dar es Salaam.It then used the Multiple-Linear Regression models for environmental risk prediction.Furthermore,the study used the elimination and choice expressing reality(ELECTRE)method to analyze the most efficient waste treatment options,particularly scenarios with the lowest economic and environmental costs(Ec C and En C,respectively).Afterward,it combined a geographical information system(GIS)with MCD-AHP to objectively assess the area suitability level to determine the optimal solid waste disposal facilities(SWDFs)through the computation of site suitability indices(SSIs)to identify the site suitability levels(SSLs)for the whole of Dar es Salaam area.Finally,the study used information from the previously investigated subjects(objectives)and conduct various controlled surveys to establish a database applied in simulation for proposing an ISWM for the city.Regarding the generation state,the WGRs in Dar es Salaam is rapidly increasing,while the available response and management system is not capable of keeping the pace.From the observed data,the measure of WGRs in 2019 stands at 5.8x10³MT/day which is about a 50%increase from 3.9x10³in 2006.The MLP-ANN models which formed the best prediction models for WGRs in Dar es Salaam showed that the WGRs in this area will double in less than 20 years.With the current trend where approximately 50%of the generated waste is left unattended,the ERI displays an upward trend with some fluctuations throughout the study period(2006–2019).The lowest risk value(0.35)was observed in 2006.This value was within risk level II(0.2–0.4),denoting a relatively low-risk level.On the other hand,the highest risk value(0.56)was observed in 2015.This value is within risk level III(0.4–0.6),signifying the medium risk level.An estimation on the environmental risk prediction of the critical point showed that with the influence of the major contributing indices,without any positive changes in the response index,the environmental risk level(ERL)will enter a relatively high-risk level(Level IV)in 2025and about in 2038 will reach the critical point of extremely high-risk level(Level V).Besides,the major contributing indices:pressure,state,and impact which are currently close to or already in Level IV,will reach the critical point in a relatively short time than the comprehensive ERI,i.e.,2022,2025,and 2030,respectively.Regarding the ideal SWM option,the dominant scenario that formed the core for all considered options was found.It costs around$274,100 while saving about 1585 metric tons(MT)of CO₂ emissions daily.This scenario suggests that after all the SW generated in Dar es Salaam is collected and segregated,food-based organic waste should be composted whilst plastic,paper-based organic waste,glass,and ferrous metal should be recycled.After treatment,other remaining wastes will go to some forms of landfills.Regarding SSL the final suitability map produced indicates that a large part of the study area(60.92%)is completely unsuitable for siting SWDFs and landfills in particular.The remaining areas consisted of a land with varying suitability levels,which was grouped into four classes:very low(30.92%),low(2.05%),moderate(5.65%),and high(0.46%).To this end,only the high suitability class(0.46%)were of acceptable suitability levels(SSI?0.2 in a 0.01 to 0.25 SS scale).This indicates that Dar es Salaam land is limited with less than 0.5%of its total landmass acceptable for landfill siting.Despite this concern,the study is optimistic about the available opportunities from SW.It proposed an ISWM system based on the 3R approach that focuses on the application of modern technology and environmentally friendly techniques,considering the circular economy agenda of waste to resources/energy for sustainable SWM.Among the major innovation points in this study,it combined Multi-Layer Perceptron Artificial Neuron Network(MLP-ANN),the mimic of the human biological nervous system to study environmental systems and SWM in particular.This is particularly new in the SW industry and helped to obtain a new means of dealing with the waste problem especially in low-income countries for comprehensive environmental risk reduction.