Optimization Model for Mitigating Global Warming at the Farm Scale: An Application to Japanese Rice Farms
AbstractIn Japan, greenhouse gas emissions from rice production, especially CH4 emissions in rice paddy fields, are the primary contributors to global warming from agriculture. When prolonged midseason drainage for mitigating CH4 emissions from rice paddy fields is practiced with environmentally friendly rice production based on reduced use of synthetic pesticides and chemical fertilizers, Japanese rice farmers can receive an agri-environmental direct payment. This paper examines the economic and environmental effects of the agri-environmental direct payment on the adoption of a measure to mitigate global warming in Japanese rice farms using a combined application of linear programming and life cycle assessment at the farm scale. Eco-efficiency, which is defined as net farm income divided by global warming potential, is used as an integrated indicator for assessing the economic and environmental feasibilities. The results show that under the current direct payment level, the prolonged midseason drainage technique does not improve the eco-efficiency of Japanese rice farms because the practice of this technique in environmentally friendly rice production causes large economic disadvantages in exchange for small environmental advantages. The direct payment rates for agri-environmental measures should be determined based on the condition that environmentally friendly agricultural practices improve eco-efficiency compared with conventional agriculture. View Full-Text
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Masuda, K. Optimization Model for Mitigating Global Warming at the Farm Scale: An Application to Japanese Rice Farms. Sustainability 2016, 8, 593.
Masuda K. Optimization Model for Mitigating Global Warming at the Farm Scale: An Application to Japanese Rice Farms. Sustainability. 2016; 8(7):593.Chicago/Turabian Style
Masuda, Kiyotaka. 2016. "Optimization Model for Mitigating Global Warming at the Farm Scale: An Application to Japanese Rice Farms." Sustainability 8, no. 7: 593.
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