Financing Green Electricity in Nigeria for Economic Growth

Green finance connotes the financial activities designed to aid the recovery of the environment from degradation. In Nigeria, the danger posed by solid waste to the environment is enormous. In particular, refuse collection and disposal mechanisms have not been adequately executed. The urban landscapes in the country are littered with plastics, polythene, and various non-degradable materials. In this chapter, the authors present an efficient way to clean up the Nigerian environment of solid wastes through a waste-to-energy strategy by exploring the green finance options or sources and structure to deliver renewable and clean electricity for Nigeria. The authors concluded by highlighting that green finance is useful for efficient waste management and the generation of green electricity to the Nigerian national grid.

Sustainable City: Energy Usage Prediction Method for Electrified Refuse Collection Vehicles

With the initiative of sustainable smart city space, services and structures (3S), progress towards zero-emission municipal services has advanced the deployment of electric refuse collection vehicles (eRCVs). However, eRCVs are commonly equipped with oversized batteries which not only contribute to the majority of the weight of the vehicles but also remain a consistent weight, independent of the stage of charge (SoC), thus crucially jeopardising the significance of eRCVs in sustainability and economic strategies. Hence, customising the battery capacity in such a way that minimises its weight while storing ample energy for stalwart serviceability could significantly enhance its sustainability. In this study, taking only addresses as input, through an emergent two-stage data analysis, the energy required to collect refuse from a group of addresses was predicted. Therefore, predictions of the battery capacity requirement for the target location are possible. The theories and techniques presented in this paper were evaluated using real-life data from eRCV trials. For the same group of addresses, predicted results show an averaged error rate of 8.44%, which successfully demonstrates that using the proposed address-driven energy prediction approach, the energy required to collect refuse from a set of addresses can be predicted, which can provide a means to optimise the vehicle’s battery requirement.

Assessment of the Refuse Collection Charges in Covering Waste Management Cost: The Case of ILALA Municipality -Dar Es Salaam, Tanzania

The world urban population is expected to increase by 72 per cent by 2050, to reach nearly 6 billion in 2050 from 3 billion in 2011 (UN, 2012, Hussein 2019). By mid-century the world urban population will likely be the same size as the world’s total population was in 2002 (UN, 2011, and Hussein, 2018). Although the global average in 2014 reached 54 per cent, the percentages are already around 80% in the Americas, and over 70% in Europe and Oceania, but only 48% in Asia and 40% in Africa (UN, 2014, Hussein, 2019).

Math Students help their Community develop Balanced Refuse Collection Routes

In fall of 2017, the Superintendent of Public Works for Kutztown Borough approached Kutztown University’s Department of Mathematics seeking help in “re-balancing” refuse collection routes in the Borough of Kutztown. Historically, refuse was collected two days a week on the south side (Mondays and Thursdays) of Main Street and two days a week on the north side (Tuesdays and Fridays) of Main Street. Wednesdays were used for recycling collection. Over the years, new housing development was primarily on the north side of Main Street. As a result of this development, refuse collection time had become “unbalanced”; requiring more time for the north side collection. During the spring semester 2018, several math majors in their last semester at Kutztown University developed a new refuse collection strategy. This strategy balanced collection times over the four collection days and just as importantly, minimized the modifications to the existing routes. Additionally, a minimum number of residents were impacted while accounting for future housing development. Their strategy has been successfully used in the Borough of Kutztown since August 2018.