Municipal Waste Generation and Socioeconomic Drivers

Abstract

Using data sets from Italian provinces that include rich northern and poorer southern regions, this article examines to what extent income and municipal waste generation are linked and at what level of income they become delinked. The analysis shows that the turning point occurs at very high levels of value added per capita (in the range of 22,586 to 31,611), exemplified by a very limited number of wealthy (northern) Italian provinces. The authors also find that some recently adopted waste policy and waste management instruments have influenced waste generation at source, independent of socioeconomic characteristics. This supports the argument that more effective waste management instruments that target waste prevention at the source need to be implemented in line with the stated priorities of the EU and member countries. The findings also imply that developing countries in particular should not wait to implement waste reduction policies until household incomes and consumption levels increase.

Municipal Waste Kuznets Curves: Evidence on Socio-Economic Drivers and Policy Effectiveness from the EU

“…Mazzanti et al (2008) find some WKC evidence and signs that waste management instruments do have an effect on reducing waste generation in Italy, where trends are affected by economic, policy and structural geographical differences. 5 There are also some studies on specific evaluations of the Landfill Directive-the main driver of regulatory actions in the EU, and the UK landfill tax-introduced in 1996 and one of the few cases of a real environmental tax based on evaluation of the marginal external costs.…”

Spatial distribution of usable biomass feedstock and technical bioenergy potential in China

“…Some of the existing literature has indicated that waste production has a strong positive correlation with economic T A B L E 3 LHVs of biomass feedstocks and energy conversion coefficients development and population density at a 0.1 km resolution at the municipal and provincial levels (Mazzanti, Montini, & Zoboli, 2008;Shu, Wang, & Sun, 2012;Xu, Yan, & Cui, 2013). In this research, the statistical downscaling method is used to spatialize waste based on the dataset of GDP, land-use, and the population at 1 km resolution (Li, Zhang, & Yang, 2014;Wilby et al, 1998Wilby et al, , 2004Zhu, Yang, & Zhao, 2011).…”

Waste Generation and Landfill Diversion Dynamics: Decentralised Management and Spatial Effects

“…She finds for OECD that municipal solid waste (MSW) increases monotonically with income and that urbanisation exerts an even stronger effect on waste generation, while the time-invariant policy index is not significant. At country level, Mazzanti et al (2008) analyze waste generation dynamics, showing that only the richest provinces are close to a turning point in the waste income relationship, with strong north south gaps and an effective role of waste management systems like tariffs, which are nevertheless associated to endogeneity with respect to income. Mazzanti and Zoboli (2009), based on panel data for a group of European countries, finds also neither absolute nor relative delinking, for municipal or packaging waste for 1995-2000 and 1997-2000 respectively.…”