炭素クレジットが土地利用に与える影響の予測

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  • Prediction of land-use change induced by carbon credit using a numerical model
  • タンソ クレジット ガ トチ リヨウ ニ アタエル エイキョウ ノ ヨソク

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Traditionally, land use change has involved forests being turned into farmland. However, this may change now that forestry has become recognized as a method to reduce the effects of climate change. Carbon credit systems will increase the productive value of forests which may reduce the occurrence of forested land being turned into farmland and result in the afforestation of unused land. If less forested land is turned into farmland, there is speculation that there will be complementary pressure on food production; however, detailed study has not been done on this issue. The current research involved developing a method to predict the potential of land use change upon the introduction of a carbon credit system using a numerical model. In particular, we considered conversions from forested land to farmland and the afforestation of unused land due to the introduction of a carbon credit system. First, we investigated the reasons for land use change by looking at differences in land use change that result from different scenarios. Next, we considered how land use would change as a result of introducing a carbon credit system. Finally, we investigated the effect of carbon price predictions on increases in forest areas in order to determine trends in future development. The current research differs from research involving traditional land use models because we used a mesh-based land use prediction model that uses the productivity of agriculture and forestry obtained from mesh and a global land cover map. We found that Africa was particularly sensitive to differences in land use that result from different scenarios. We also found that the introduction of a carbon credit system will reduce the amount of land that is converted to farmland and that if the carbon credits appreciate in value, there will be an even greater reduction.

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