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Global climate change - a feasibility perspective of its effect on human health at a local scale
Author(s) -
Michele Bernardi
Publication year - 2008
Publication title -
geospatial health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.545
H-Index - 36
eISSN - 1970-7096
pISSN - 1827-1987
DOI - 10.4081/gh.2008.238
Subject(s) - greenhouse gas , downscaling , climate change , livelihood , climate change mitigation , interdependence , environmental science , environmental resource management , geography , scale (ratio) , population , natural resource economics , environmental planning , climatology , economics , political science , cartography , environmental health , ecology , agriculture , medicine , archaeology , geology , law , biology
There are two responses to global climate change. First, mitigation, which actions to reduce greenhouse gas emissions and sequester or store carbon in the short-term, and make development choices that will lead to low emissions in the long-term. Second, adaptation, which involves adjustments in natural or human systems and behaviours that reduce the risks posed by climate change to people's lives and livelihoods. While the two are conceptually distinct, in practice they are very much interdependent, and both are equally urgent from a healthy population perspective. To define the policies to mitigate and to adapt to global climate change, data and information at all scales are the basic requirement for both developed and developing countries. However, as compared to mitigation, adaptation is an immediate concern for low-income countries and for small islands states, where the reduction of the emissions from greenhouse gases is not among their priorities. Adaptation is also highly location specific and the required ground data to assess the impacts of climate change on human health are not available. Climate data at high spatial resolution can be derived by various downscaling methods using historical and real-time meteorological observations but, particularly in low-income countries, the outputs are limited by the lack of ground data at the local level. In many of these countries, a negative trend in the number of meteorological stations as compared as to before 2000 is evident, while remotely-sensed imagery becomes more and more available at high spatial and temporal resolution. The final consequence is that climate change policy options in the developing world are greatly jeopardized.

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