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Purpose The objectives of this study were to assess the black soldier fly larvae (BSFL) composting potential and to analyse the quality of organic fertilizer produced for agricultural purposes. Methods The waste biodegradation was determined by varying waste feed treatment (2, 2.5, 3.0, 3.5, to 4 kg) and control treatment of (2 kg) of heterogeneous mixture of municipal organic solid waste from market, restaurant and households. Each of the setups received equal number of viable larvae (i.e. 2000) which were 5-6 days old. To analyse the nutrient concentration of the compost residues with BSFL, the substrate and final compost were evaluated based on the levels of NPK as well as the C:N ratio. To evaluate the toxic levels of the final compost in terms of heavy metals, the presence and levels of As, Cd, Fe, Pb and Ni were investigated. Results The analysis showed that there was high percentage increase of nitrogen, phosphorus and potassium levels, i.e. 41.2% (SD ± 0.71%), 32.4% (SE ± 0.2%) and 77.1% (SE ± 0.19%), respectively. It was found that the larvae degraded more than half of the total substrate within 2 weeks. The study showed a decrease in heavy metal concentrations after larvae composting. Conclusion The study revealed that the concentration of NPK increased significantly among the treatment groups. The study further revealed that some of the heavy metals under investigation had reduced to an acceptable level according to the standards of both local and international regulatory bodies.

This paper reviews the effect of applying optimization methods on the collection process of solid waste, with particular interest in mathematical programming and geographic information system approaches in developing countries. Mathematical programming approaches maximize or minimize an objective function for improvement in procedure, to ensure operational efficiency and also serve as decision support tools. They however provide partial solutions when implemented in reality and cannot fully handle road network constraints. Geographic information system approaches allow processing of additional considerations, often ignored in other methods, such as the street network modeling. Incorporating environmental pollution consideration is very challenging in this approach, the vehicle routing problem solver encountering limits for large data. For enhanced efficiency of the vehicle routing systems, studies should further focus on incorporating all network constraints, environmental pollution considerations, and impact of land use changes on routing.

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Purpose The purpose of this paper was to determine the effect of route optimization on travel distance, travel time and fuel consumption of municipal solid waste (MSW) collection trucks. Design/methodology/approach The study modeled the existing waste collection routes in three local authorities in Ghana and proposed optimal routes using Esri’s ArcGIS Network Analyst Extension. The system generated optimal distances and times were validated by subjecting collection trucks to the optimal routes. Paired sample t-test was used to analyze the differences in means of the existing and optimal outcomes. The collected data were subjected to correlation and uncertainty analyses. Findings Results from the study indicated that weekly travel distance reduced by 81.27 km, translating into saving of 4.79 percent when trucks used the optimal routes. Travel time and fuel consumption reduced by 853.59 min and 145.86 L, making savings of 14.21 and 10.81 percent, respectively. Significant differences occurred between the means of the existing and optimal routes for travel time and fuel consumption, for each of the three local authorities. Research limitations/implications The study was conducted in Ghana using data collected from three local authorities. Practical implications Significant reduction of MSW collection cost can be achieved by waste management practitioners through route optimization. Originality/value The effect of route optimization on travel distance, travel time and fuel consumption has been established. Statistical analyses of the existing and optimal outcomes of the three local authorities have been provided. The findings from this study support the hypothesis that optimal routes reduce operating cost through savings in travel distance, travel time and fuel consumption.