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Integration of WTE technologies into the electrical system for low-carbon growth in Venezuela

The present work intends to address the lack of energy access and low waste collection services through the integration of waste-to-energy (WTE) technologies into the electrical system, aiming for a low-carbon growth. A minimization of cost approach was applied using linear programming. Venezuela was used as the case study for five cases under two scenarios. In Scenario A, the current waste collection service rate was considered (88%), whereas in Scenario B, it was assumed to improve to 94%. Cases 1 to 5 were as follows: Current fuel subsidy, No fuel subsidy, Subsidies on WTE, Carbon tax policy and Carbon-reduction policy. Total carbon emissions were analysed. In all cases except for the first one, WTE technologies were present in the energy matrix, reducing carbon emissions by approximately 3–5.4 × 106 tonne of carbon. Furthermore, a difference of 1–2 × 106 tonne of carbon between scenarios was observed. The last two cases achieved higher emission reductions with an abatement cost of $169 tC−1 and $89 tC−1, respectively. Despite the lower abatement cost of the carbon reduction policy, this research proposes the implementation of a carbon tax because it could finance the improvement of waste management practices.
- Tohoku University Japan
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).9 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
