Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture
Coupling biophysical and micro-economic models to assess the effect of mitigation measures on greenhouse gas emissions from agriculture
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耦合生物物理和微观经济模型来评估缓解措施对农业温室气体排放的影响
DOI：
10.1007/s10584-009-9653-8
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发表时间：
2010
期刊：
影响因子：
4.8
通讯作者：
C. Le Bas
中科院分区：
文献类型：
--
作者：
S. Durandeau;B. Gabrielle;C. Godard;P. Jayet;C. Le Bas
农业土壤是大气一氧化二氮（N2 O）的主要来源，一种潜在的温室气体（GHG）。由于N2 O排放量强烈依赖于土壤类型，气候和作物管理，其库存需要结合生物物理和经济建模，以模拟农民的行为。在这里，我们耦合的生物物理土壤-作物模型，CERES-EGC，与经济农场型供应模型，AROPAj，在区域尺度在北方法国。利用CERES-EGC软件生成N2 O排放对氮肥输入的响应曲线，并进行线性化处理，得到排放因子。后者的范围为0.001至0.0225 kg N2 O-N kg-1 Nf，具体取决于土壤和作物类型，而IPCC指南的固定值为0.0125。模拟的排放因子被输入到经济模型AROPAj中，该模型将农场一级的温室气体排放与生产因素联系起来。这导致N2 O排放量比默认IPCC方法低20%。减少农业温室气体排放的成本是使用对温室气体排放的第一最佳税收和对其假定因素（牲畜规模和肥料投入）的第二最佳税收计算的。第一个最好的税收是相对有效的，实现了8%的减少，税收为11欧元/吨CO2当量，而第二个最好的方案为68欧元/吨CO2当量。
Agricultural soils are a major source of atmospheric nitrous oxide (N2O), a potent greenhouse gas (GHG). Because N2O emissions strongly depend on soil type, climate, and crop management, their inventory requires the combination of biophysical and economic modeling, to simulate farmers’ behavior. Here, we coupled a biophysical soil-crop model, CERES-EGC, with an economic farm type supply model, AROPAj, at the regional scale in northern France. Response curves of N2O emissions to fertilizer nitrogen (Nf) inputs were generated with CERES-EGC, and linearized to obtain emission factors. The latter ranged from 0.001 to 0.0225 kg N2O-N kg − 1 Nf, depending on soil and crop type, compared to the fixed 0.0125 value of the IPCC guidelines. The modeled emission factors were fed into the economic model AROPAj which relates farm-level GHG emissions to production factors. This resulted in a N2O efflux 20% lower than with the default IPCC method. The costs of abating GHG emissions from agriculture were calculated using a first-best tax on GHG emissions, and a second-best tax on their presumed factors (livestock size and fertilizer inputs). The first-best taxation was relatively efficient, achieving an 8% reduction with a tax of 11 €/ t-CO2-equivalent, compared to 68 €/t-CO2 eq for the same target with the second-best scheme.