Sustainable Development Goals Data-Driven Local Policy: Focus on SDG 11 and SDG 12

Abstract

Municipal solid waste charging schemes can be powerful drivers for local policy efforts in reaching the goals of the 2030 Agenda for Sustainable Development adopted by all United Nations Member States in 2015. This paper aims to provide empirical evidence on an economic lever to meet SDG 11, Target 11.6 and SDG 12, Target 12.5 by applying the polluter-pays principle to waste management that also depends on user engagement through modern incentivizing charging systems. Unit pricing schemes in municipal solid waste management are often associated with a higher percentage of separated waste, less per capita waste production, and reduced service costs. We checked whether unit pricing schemes and the percentage of the sorted waste collection were correlated, assessed whether there is an impact on per capita waste generation, examined the impact on the total cost of management, and explored how specific phases of waste management were affected. The analysis was based on an empirical sample of 1,636 municipalities, of which 506 had unit pricing schemes in place. Our results confirm that unit pricing schemes can be associated with a higher percentage of sorted waste collection and less per capita waste generation. The impact of unit pricing on the total cost of management was not found to be significant, probably due to different impacts on specific services and phases of waste management. The policy implications are as follows: it is suggested that public administrators put data-driven policy targets into government programs that are applied at an operational level by competent municipal civil servants and codified into single programming documents for contracting waste management utilities according to SDG 11 Target 11.6 and SDG 12 Target 12.5.

Designing Circular Economy-Compliant Municipal Solid Waste Management Charging Schemes

“…4 is consistent with previous literature, in which UCSs are associated with higher environmental performance (+4%) and lower per capita generation of MSW (− 12 kg). Considering the cost of MSW management, however, the SCS and UPS are similar (Beccarello and Di Foggia, 2022). Regarding the circumstances in which UCSs may fail to achieve the desired targets, it is possible to speculate that there is an impact of UCSs on total costs; however, the impact is less when the analysis is narrowed to the subsample of more comparable territories.…”

A Circularity Mapping Framework for Urban Policymaking

“…Since urban life's environmental, economic, social, and cultural aspects are intertwined, only an integrated strategy can result in successful urban sustainable development (Bote Alonso et al, 2022;Prendeville et al, 2018). Local policies must be integrated with those that support environmental protection, social inclusion, economic development, and, in particular, SDGs (Beccarello & Di Foggia, 2022b).…”

Harnessing a Better Future: Exploring AI and ML Applications in Renewable Energy

“…SDG 8 is advanced via the creation of job opportunities in the area of renewable energy, while SDG 9 is advanced through the promotion of scientific developments in the production and consumption of biofuels. Both of these goals are advanced through the inclusion into the energy mix [6], [23], [223].…”

“…This enables governments, companies, and communities to make educated decisions that align with the SDGs and contribute to the achievement of net-zero emissions [18]- [20]. Integrating machine learning with the SDGs and net-zero objectives provides a potent way to address urgent global concerns and drive substantial progress toward a more sustainable and resilient future for everyone [21]- [23].…”