Condiciones de trabajo y morbilidad percibidas entre mineros de carbón en Guachetá, Colombia

Introducción: En Colombia la investigación sobre condiciones de trabajo y salud en minería carbonífera es escasa y no considera la percepción de la población expuesta y sus comportamientos frente a los riesgos inherentes. Objetivo: Determinar la asociación entre las condiciones de trabajo y morbilidad percibidas entre trabajadores de minas de carbón en Guachetá, Cundinamarca. Materiales y métodos: Se realizó un estudio transversal con 154 trabajadores seleccionados aleatoriamente del total registrado en la alcaldía municipal. Se indagó sobre características sociodemográficas, condiciones de trabajo y salud en las minas. Se estimaron prevalencias de los trastornos respiratorios, osteomusculares y auditivos, y se exploraron las asociaciones entre algunas condiciones de trabajo y los eventos con prevalencia superior a 30% de forma bivariada y múltiple, con regresiones Poisson con varianza robusta. Resultados: Los trabajadores fueron en su mayoría hombres, con edades entre 18 y 77 años de edad. Los problemas de salud más frecuentemente reportados fueron dolor lumbar (46,10%), dolor del miembro superior (40,26%), dolor del miembro inferior (34,42%), trastornos respiratorios (17,53%) y problemas auditivos (13,64%). Existen diferencias importantes en la percepción dependiendo de la antigüedad laboral y las condiciones subterráneas o no del trabajo. Conclusión: Los riesgos más reconocidos por los trabajadores son los relacionados con trastornos osteomusculares, al parecer por ser más evidentes en su cotidianidad. Las acciones en salud ocupacional podrán considerar estos hallazgos en sus planes de prevención de la enfermedad en las minas del carbón colombianas.

Remesas y desarrollo económico. Un análisis empírico del caso mexicano

El objetivo de este trabajo es contribuir a identificar el efecto de las remesas que envían los emigrantes a sus comunidades de origen en México. Del mismo modo, se estudia el efecto que la participación de la mujer tiene en este proceso. La fuente de información es el Consejo Nacional de Población de México CONAPO y contiene variables a nivel estatal y municipal para el año 2000. La base de datos contiene índices de desarrollo humano, intensidad migratoria y remesas para los 2443 municipios mexicanos. La evidencia empírica sugiere que las remesas tienen un impacto positivo sobre los niveles de desarrollo de las comunidades receptoras. No obstante, la relación entre remesas y desarrollo es no lineal. Adicionalmente, se en contró que el efecto positivo que tienen las remesas sobre el desarrollo es más alto cuando la cabeza de familia de los hogares receptores es mujer.

Desterrando minas

Desterrando minas es, a su vez, un documental de contexto y un documental de proceso. A partir de la inmersión en los mismos campamentos en los que viven los desminadores se cuenta la historia de Nariño como la vivieron sus pobladores, se muestra la manera en la que el miedo fue el principal configurador de las relaciones entre la comunidad y su territorio y cómo el desminado ha transformado ese miedo

Iniciación a la gestión medioambiental

Libro de apoyo a la docencia - 166 p.

The Assault on Human Rigths and the Resilience of the Andean Dream: Health Inequities in Ecuador. IV Annual Distinguished Lecture sponsored by the Center for Research on Ethnicity, Culture and Health; School of Public Health; University of Michigan

The point of departure for these reflections is life, since its protection is the central purpose encouraging the defense of human rights and of public health. Life in the Andes has an exceptional diversity. Particularly in Ecuador, my country, this diversity constitutes a characteristic sign that is expressed in two main forms: natural megadiversity and multiculturalism. Indeed, Ecuador’s small territory synthesizes practically all types of lifezones that exist on Earth, having received the gift of high average rates of solar energy and abundant nutritional sources, which have facilitated the natural reproduction of countless species that show their beautiful vitality in the variety of ecosystems that compose the Andean mountain range, the tropical plains, the Amazon humid forests, and the Galapagos Islands. But besides being a highly biodiverse country, it is also a plurinational and multi-cultural society, in which the activity of human beings, organized into social conglomerates of different historical and cultural backgrounds, have formed more than a dozen nations and peoples. Regrettably this natural and human wealth has not been able to bear its best fruits due to the violent operation of a deep social inequity – unfortunately also one of the highest in the Americas—which conspires against life and is reproduced in national and international inequitable relations. This structural inequity has changed its form throughout the centuries and currently has reached its highest and most perverse level of development.

Integrated modelling of climate change impacts on water resources and quality in a lowland catchment: River Kennet, UK

An integrated approach to climate change impact assessment is explored by linking established models of regional climate (SDSM), water resources (CATCHMOD) and water quality (INCA) within a single framework. A case study of the River Kennet illustrates how the system can be used to investigate aspects of climate change uncertainty, deployable water resources, and water quality dynamics in upper and lower reaches of the drainage network. The results confirm the large uncertainty in climate change scenarios and freshwater impacts due to the choice of general circulation model (GCM). This uncertainty is shown to be greatest during summer months as evidenced by large variations between GCM-derived projections of future tow river flows, deployable yield from groundwater, severity of nutrient flushing episodes, and Long-term trends in surface water quality. Other impacts arising from agricultural land-use reform or delivery of EU Water Framework Directive objectives under climate change could be evaluated using the same framework. (c) 2006 Elsevier B.V. All rights reserved.

Statistical downscaling of river flows

An extensive statistical ‘downscaling’ study is done to relate large-scale climate information from a general circulation model (GCM) to local-scale river flows in SW France for 51 gauging stations ranging from nival (snow-dominated) to pluvial (rainfall-dominated) river-systems. This study helps to select the appropriate statistical method at a given spatial and temporal scale to downscale hydrology for future climate change impact assessment of hydrological resources. The four proposed statistical downscaling models use large-scale predictors (derived from climate model outputs or reanalysis data) that characterize precipitation and evaporation processes in the hydrological cycle to estimate summary flow statistics. The four statistical models used are generalized linear (GLM) and additive (GAM) models, aggregated boosted trees (ABT) and multi-layer perceptron neural networks (ANN). These four models were each applied at two different spatial scales, namely at that of a single flow-gauging station (local downscaling) and that of a group of flow-gauging stations having the same hydrological behaviour (regional downscaling). For each statistical model and each spatial resolution, three temporal resolutions were considered, namely the daily mean flows, the summary statistics of fortnightly flows and a daily ‘integrated approach’. The results show that flow sensitivity to atmospheric factors is significantly different between nival and pluvial hydrological systems which are mainly influenced, respectively, by shortwave solar radiations and atmospheric temperature. The non-linear models (i.e. GAM, ABT and ANN) performed better than the linear GLM when simulating fortnightly flow percentiles. The aggregated boosted trees method showed higher and less variable R2 values to downscale the hydrological variability in both nival and pluvial regimes. Based on GCM cnrm-cm3 and scenarios A2 and A1B, future relative changes of fortnightly median flows were projected based on the regional downscaling approach. The results suggest a global decrease of flow in both pluvial and nival regimes, especially in spring, summer and autumn, whatever the considered scenario. The discussion considers the performance of each statistical method for downscaling flow at different spatial and temporal scales as well as the relationship between atmospheric processes and flow variability.

A review of climate risk information for adaptation and development planning

Although the use of climate scenarios for impact assessment has grown steadily since the 1990s, uptake of such information for adaptation is lagging by nearly a decade in terms of scientific output. Nonetheless, integration of climate risk information in development planning is now a priority for donor agencies because of the need to prepare for climate change impacts across different sectors and countries. This urgency stems from concerns that progress made against Millennium Development Goals (MDGs) could be threatened by anthropogenic climate change beyond 2015. Up to this time the human signal, though detectable and growing, will be a relatively small component of climate variability and change. This implies the need for a twin-track approach: on the one hand, vulnerability assessments of social and economic strategies for coping with present climate extremes and variability, and, on the other hand, development of climate forecast tools and scenarios to evaluate sector-specific, incremental changes in risk over the next few decades. This review starts by describing the climate outlook for the next couple of decades and the implications for adaptation assessments. We then review ways in which climate risk information is already being used in adaptation assessments and evaluate the strengths and weaknesses of three groups of techniques. Next we identify knowledge gaps and opportunities for improving the production and uptake of climate risk information for the 2020s. We assert that climate change scenarios can meet some, but not all, of the needs of adaptation planning. Even then, the choice of scenario technique must be matched to the intended application, taking into account local constraints of time, resources, human capacity and supporting infrastructure. We also show that much greater attention should be given to improving and critiquing models used for climate impact assessment, as standard practice. Finally, we highlight the over-arching need for the scientific community to provide more information and guidance on adapting to the risks of climate variability and change over nearer time horizons (i.e. the 2020s). Although the focus of the review is on information provision and uptake in developing regions, it is clear that many developed countries are facing the same challenges. Copyright © 2009 Royal Meteorological Society

The budget and the WTO: driving forces behind the ‘Health Check’?

The chapter examines the evidence for budget concerns or external (WTO) pressures being the drivers for the 'Health Check' reform of the European Union's common agricultural policy.

Considering the normative, systemic and procedural dimensions in indicator-based sustainability assessments in agriculture

This paper develops a framework for evaluating sustainability assessment methods by separately analyzing their normative, systemic and procedural dimensions as suggested by Wiek and Binder [Wiek, A, Binder, C. Solution spaces for decision-making – a sustainability assessment tool for city-regions. Environ Impact Asses Rev 2005, 25: 589-608.]. The framework is then used to characterize indicator-based sustainability assessment methods in agriculture. For a long time, sustainability assessment in agriculture has focused mostly on environmental and technical issues, thus neglecting the economic and, above all, the social aspects of sustainability, the multifunctionality of agriculture and the applicability of the results. In response to these shortcomings, several integrative sustainability assessment methods have been developed for the agricultural sector. This paper reviews seven of these that represent the diversity of tools developed in this area. The reviewed assessment methods can be categorized into three types: (i) top-down farm assessment methods; (ii) top-down regional assessment methods with some stakeholder participation; (iii) bottom-up, integrated participatory or transdisciplinary methods with stakeholder participation throughout the process. The results readily show the trade-offs encountered when selecting an assessment method. A clear, standardized, top-down procedure allows for potentially benchmarking and comparing results across regions and sites. However, this comes at the cost of system specificity. As the top-down methods often have low stakeholder involvement, the application and implementation of the results might be difficult. Our analysis suggests that to include the aspects mentioned above in agricultural sustainability assessment, the bottomup, integrated participatory or transdisciplinary methods are the most suitable ones.

Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation

Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

Energy

The impact of energy policy measures has been assessed with various appraisal and evaluation tools since the 1960s. Decision analysis, environmental impact assessment and strategic environmental assessment are all notable examples of progenitors of Regulatory Impact Assessment (RIA) in the assessment of energy policies, programmes and projects. This chapter provides overview of policy tools which have been historically applied to assess the impacts of energy policies, programmes and projects. It focuses on the types of data and models that typically inform RIAs for energy policies; the organisations involved; and issues of data exchange between energy companies and policy-makers. Examples are derived from the European Commission, the UK, Italy, the Netherlands and France. It is concluded that the technical and economic analysis underpinning RIAs on energy policy and regulation varies significantly depending on the type of organisation carrying them out.

A Spatial-Temporal Downscaling Approach To Construction Of Rainfall Intensity-Duration-Frequency Relations In The Context Of Climate Change

This paper proposes a spatial-temporal downscaling approach to construction of the intensity-duration-frequency (IDF) relations at a local site in the context of climate change and variability. More specifically, the proposed approach is based on a combination of a spatial downscaling method to link large-scale climate variables given by General Circulation Model (GCM) simulations with daily extreme precipitations at a site and a temporal downscaling procedure to describe the relationships between daily and sub-daily extreme precipitations based on the scaling General Extreme Value (GEV) distribution. The feasibility and accuracy of the suggested method were assessed using rainfall data available at eight stations in Quebec (Canada) for the 1961-2000 period and climate simulations under four different climate change scenarios provided by the Canadian (CGCM3) and UK (HadCM3) GCM models. Results of this application have indicated that it is feasible to link sub-daily extreme rainfalls at a local site with large-scale GCM-based daily climate predictors for the construction of the IDF relations for present (1961-1990) and future (2020s, 2050s, and 2080s) periods at a given site under different climate change scenarios. In addition, it was found that annual maximum rainfalls downscaled from the HadCM3 displayed a smaller change in the future, while those values estimated from the CGCM3 indicated a large increasing trend for future periods. This result has demonstrated the presence of high uncertainty in climate simulations provided by different GCMs. In summary, the proposed spatial-temporal downscaling method provided an essential tool for the estimation of extreme rainfalls that are required for various climate-related impact assessment studies for a given region.