Impact of a value chain approach on the sustainability of solid waste management in Mukuru Kwa njenga informal settlements Nairobi, Kenya

En un mundo altamente urbanizado, la gestión de residuos sólidos es un problema primordial en toda ciudad. Las ciudades de paises en desarrollo deben además afrontar retos que no afectan a las ciudades de paises desarrollados. En los paises en desarrollo muchas municipalidades sufren un crecimiento descontrolado de los asentamientos informales sin planificación urbana que hace muy complicada una adecuada gestión de los residuos sólidos urbanos, situación que se agrava al no contar estas con suficientes recursos económicos para llevar a cabo su responsabilidad en cuanto a provisión del sevicio básico de recogida de residuos. La provisión de servicio de recogida de residuos por parte de SHGs (grupos de ayuda comunitarios) en estos asentamientos informales puede ayudar a resolver algunos de estos problemas. Para que esta oportunidad sea completamente explotada, los ingresos de estos grupos deben ser garantizados, teniendo en cuenta que la sostenibilidad de estos grupos depende enteramente de ello. Este estudio pretende averiguar cómo un enfoque de cadena de valor puede mejorar la sostenibilidad de la gestión de residuos sólidos, permitiendo asegurar los ingresos de los recolectores informales de residuos. El estudio propondrá después de analizado el actual sistema, mejoras que permitan desarrollar un medio ambiente saludable en los asentamientos informales donde se desarrolla el estudio. Para alcanzar este objetivo, se ha desarrollado una investigación específica en Nairobi (Kenia) en el asentamiento precario de Mukuru Kwa Njenga, analizando los distintos aspectos relevantes que tienen influencia en una gestión integrada de residuos sólidos y las relaciones entre los distintos actores que tienen influencia en la misma.

Economic impacts of climate change on agrifood markets: A bio-economic approach with a focus on the EU

Projections for world food production and prices play a crucial role to evaluate and tackle future food security challenges. Understanding how these projections will be affected by climate change is the main objective of this study. By means of a bio-economic approach we assess the economic impacts of climate change on agrifood markets, providing both a global analysis and a regionalised evaluation within the EU. To account for uncertainty, we analyse the IPCC emission scenario A1B for the 2030 horizon under several simulation scenarios that differ in (1) the climate projection, from HadleyCM3 (warm) or ECHAM5 (mild) global circulation models; and (2) the influence of CO2 effects. Results of this study indicate that agrifood market projections to 2030 are very sensitive to climate change uncertainties and, in particular to the magnitude of the carbon fertilization effect.

An integrated modeling approach to assess the impact on road freight transport demand of allowing longer and heavier vehicles (LHVs) in Spain

The assessment on introducing Longer and Heavier Vehicles (LHVs) on the road freight transport demand is performed in this paper by applying an integrated modeling approach composed of a Random Utility-Based Multiregional Input-Output model (RUBMRIO) and a road transport network model. The approach strongly supports the concept that changes in transport costs derived from the LHVs allowance as well as the economic structure of regions have both direct and indirect effects on the road freight transport system. In addition, we estimate the magnitude and extent of demand changes in the road freight transportation system by using the commodity-based structure of the approach to identify the effect on traffic flows and on pollutant emissions over the whole network of Spain by considering a sensitivity analysis of the main parameters which determine the share of Heavy-Goods Vehicles (HGVs) and LHVs. The results show that the introduction of LHVs will strengthen the competitiveness of the road haulage sector by reducing costs, emissions, and the total freight vehicles required.

A Fuzzy approach based on dynamic programming and metaheuristics for selecting safeguards for risk management for information systems

In this paper we focus on the selection of safeguards in a fuzzy risk analysis and management methodology for information systems (IS). Assets are connected by dependency relationships, and a failure of one asset may affect other assets. After computing impact and risk indicators associated with previously identified threats, we identify and apply safeguards to reduce risks in the IS by minimizing the transmission probabilities of failures throughout the asset network. However, as safeguards have associated costs, the aim is to select the safeguards that minimize costs while keeping the risk within acceptable levels. To do this, we propose a dynamic programming-based method that incorporates simulated annealing to tackle optimizations problems.