Technical co-operation for the development of small-scale industries

Includes bibliography

Small-scale industry in Trinidad and Tobago

Includes bibliography

Report of a Meeting on Small-Scale Agro-Processing Activities in the Organization of Eastern Caribbean States

Includes bibliography

Linkages between agro-industry and small-scale agriculture in Guyana

Includes bibliography

Agroindustrial linkages for the improvement of small-scale farming in Jamaica

Includes bibliography

Agroindustry and small-scale agriculture: a comparative synthesis of different experiences

Includes bibliography

Agroindustry and small-scale agriculture: conceptual guidelines for a policy to encourage linkage between them

Includes bibliography

Small-scale landfills: impacts on groundwater and soil

In Brazil, the large quantities of solid waste produced are out of step with public policies, technological developments, and government budgets for the division. In small municipalities, the common lack of technological knowledge and financial conditions for suitable waste disposal has resulted in a large number of illegal dumps. Therefore, small sanitary landfill facilities are working with simplified operations focusing on cost reduction and meeting the economic and technological standards of the city without endangering the environment or public health. Currently, this activity is regulated at a federal level although there is some uncertainty regarding the risk of soil and aquifer contamination as theses facilities do not employ liners. Thus, this work evaluates a small landfill to identify changes in soil and groundwater using geotechnical parameters, monitoring wells, and geophysical tests performed by electrical profiling. It is verified that based on current conditions, no contaminants have migrated via underground water aquifers, and overall no significant changes have occurred in the soil. It is concluded that, despite its simplicity, the method investigated is a viable alternative for the final disposal of municipal solid waste from small cities, especially in developing countries.

Bony fishes (Teleostei) caught by small-scale fisheries off central to south coast of São Paulo State, Southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A unified solution to the small scale problems of the Lambda CDM model II: introducing parent-satellite interaction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Motion-based wave estimation: Small-scale tests with a crane-barge model

This paper provides additional validation to the problem of estimating wave spectra based on the first-order motions of a moored vessel. Prior investigations conducted by the authors have attested that even a large-volume ship, such as an FPSO unit, could be adopted for on-board estimation of the wave field. The obvious limitation of the methodology concerns filtering of high-frequency wave components, for which the vessel has no significant response. As a result, the estimation range is directly dependent on the characteristics of the vessel response. In order to extend this analysis, further small-scale tests were performed with a model of a pipe-laying crane-barge. When compared to the FPSO case, the results attest that a broader range of typical sea states can be accurately estimated, including crossed-sea states with low peak periods. (C) 2012 Elsevier Ltd. All rights reserved.

Too Big to Ignore: Global Partnership on Small-Scale Fisheries Research - the Latin America and Caribbean network

Too Big to Ignore (TBTI; www.toobigtoignore.net) is a research network and knowledge mobilization partnership established to elevate the profile of small-scale fisheries (SSF), to argue against their marginalization in national and international policies, and to develop research and governance capacity to address global fisheries challenges. Network participants and partners are conducting global and comparative analyses, as well as in-depth studies of SSF in the context of local complexity and dynamics, along with a thorough examination of governance challenges, to encourage careful consideration of this sector in local, regional and global policy arenas. Comprising 15 partners and 62 researchers from 27 countries, TBTI conducts activities in five regions of the world. In Latin America and the Caribbean (LAC) region, we are taking a participative approach to investigate and promote stewardship and self-governance in SSF, seeking best practices and success stories that could be replicated elsewhere. As well, the region will focus to promote sustainable livelihoods of coastal communities. Key activities include workshops and stakeholder meetings, facilitation of policy dialogue and networking, as well as assessing local capacity needs and training. Currently, LAC members are putting together publications that examine key issues concerning SSF in the region and best practices, with a first focus on ecosystem stewardship. Other planned deliverables include comparative analysis, a regional profile on the top research issues on SSF, and a synthesis of SSF knowledge in LAC

Ensemble forecasting in the Mediterranean sea

A new methodology is being devised for ensemble ocean forecasting using distributions of the surface wind field derived from a Bayesian Hierarchical Model (BHM). The ocean members are forced with samples from the posterior distribution of the wind during the assimilation of satellite and in-situ ocean data. The initial condition perturbations are then consistent with the best available knowledge of the ocean state at the beginning of the forecast and amplify the ocean response to uncertainty only in the forcing. The ECMWF Ensemble Prediction System (EPS) surface winds are also used to generate a reference ocean ensemble to evaluate the performance of the BHM method that proves to be eective in concentrating the forecast uncertainty at the ocean meso-scale. An height month experiment of weekly BHM ensemble forecasts was performed in the framework of the operational Mediterranean Forecasting System. The statistical properties of the ensemble are compared with model errors throughout the seasonal cycle proving the existence of a strong relationship between forecast uncertainties due to atmospheric forcing and the seasonal cycle.

Sea-Level climate variability in the Mediterranean Sea

Sea-level variability is characterized by multiple interacting factors described in the Fourth Assessment Report (Bindoff et al., 2007) of the Intergovernmental Panel on Climate Change (IPCC) that act over wide spectra of temporal and spatial scales. In Church et al. (2010) sea-level variability and changes are defined as manifestations of climate variability and change. The European Environmental Agency (EEA) defines sea level as one of most important indicators for monitoring climate change, as it integrates the response of different components of the Earths system and is also affected by anthropogenic contributions (EEA, 2011). The balance between the different sea-level contributions represents an important source of uncertainty, involving stochastic processes that are very difficult to describe and understand in detail, to the point that they are defined as an enigma in Munk (2002). Sea-level rate estimates are affected by all these uncertainties, in particular if we look at possible responses to sea-level contributions to future climate. At the regional scale, lateral fluxes also contribute to sea-level variability, adding complexity to sea-level dynamics. The research strategy adopted in this work to approach such an interesting and challenging topic has been to develop an objective methodology to study sea-level variability at different temporal and spatial scales, applicable in each part of the Mediterranean basin in particular, and in the global ocean in general, using all the best calibrated sources of data (for the Mediterranean): in-situ, remote-sensig and numerical models data. The global objective of this work was to achieve a deep understanding of all of the components of the sea-level signal contributing to sea-level variability, tendency and trend and to quantify them.