857 resultados para socioeconomic drivers


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Maharashtra stands third in fish production in India, with an estimated annual landings of 3.32 lakhs tonnes (1986-87). About 45% of the fishermen are directly involved in fishing. Mechanisation has boosted fish production resulting in gainful employment and higher incomes to fishermen. However, traditional fishermen along Thane creek and who entirely depend on fishing for their livelihood are comparatively poor due to their dependence on subsistence fishing and reduction of fish stock due to pollution of the creek. Conservation of the resources, proper monitoring of pollution and financial assistance and guidance will help the fishermen improve their living conditions.

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Nine different categories of stakeholders in shrimp farming industry ·were assessed to show the socioeconomic impact of shrimp farming in south-west Bangladesh. Among all the stakeholders the shrimp farmer's average own land was 4 ha whereas the seed collectors and faria's had lowest amount of average land, 0.1 and 0.5 ha respectively. The shrimp farming positively impacted to the livelihood of stakeholders. Income of the coastal people, sanitation, working facilities of women, employment, health condition and the literacy rate increased due to shrimp farming. On the other hand shrimp farming had negative impact on the rice production, livestock, drinking water supply, and social conflict and violence had increased due to shrimp farming. There were internal conflicts between different stakeholders; the farias conflict with the depot owners and shrimp farmers, marginal farmers' conflict with the rich shrimp farmers about leasing lands and saline water control, the rice farmers conflicts with the shrimp farmers about agricultural crop production.

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The paper discusses the socioeconomic effects of intensive aquaculture which is in conflict with other forms of coastal development, such as industrial development, natural fisheries, tourism and recreation, and nature conservation.

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This report was based on fieldwork conducted by trainees at the Socio-economic Monitoring (SocMon) workshop held at Vidathaltivu, Mannar Region. Topics included: community infrastructure; coastal and marine activities; and governance of marine and coastal areas

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We present a map of the transformation of energy in China as a Sankey diagram. After a review of previous work, and a statement of methodology, our main work has been the identification, evaluation, and treatment of appropriate data sources. This data is used to construct the Sankey diagram, in which flows of energy are traced from energy sources through end-use conversion devices, passive systems and final services to demand drivers. The resulting diagram provides a convenient and clear snapshot of existing energy transformations in China which can usefully be compared with a similar global analysis and which emphasises the potential for improvements in energy efficiency in 'passive systems'. More broadly, it gives a basis for examining and communicating future energy scenarios, including changes to demand, changes to the supply mix, changes in efficiency and alternative provision of existing services. © 2012 Elsevier Ltd.

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This study investigates the key drivers affecting emission increases in terms of population growth, economic growth, industrial transformation, and energy use in six Chinese megacities: Beijing, Shanghai, Tianjin, Chongqing, Guangzhou, and Hong Kong. The six cities represent the most-developed regions in China and they have similar per capita carbon dioxide (CO 2) emissions as many developed countries. There is an urgent need to quantify the magnitude of each factor in driving the emissions changes in those cities so that a potential bottom-up climate mitigation policy design at the city and sectoral levels can be initiated. We adopt index decomposition analysis and present the results in both additive and multiplicative approaches to reveal the absolute and relative levels of each factor in driving emission changes during 1985-2007. Among all cities, economic effect and energy intensity effect have always been the two dominant factors contributing to the changes in carbon emissions. This study reveals that there are large variations in the ways driving forces contribute to emission levels in different cities and industrial sectors. © 2012 by Yale University.