不同地区城镇居民收入对食品消费水足迹的影响——基于QUAIDS模型
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杨鑫, 穆月英
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Impact of urban residential income on consumptive water footprints of food in different regions based on QUAIDS modeling
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Xin YANG, Yueying MU
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| 表5 收入及食品价格对城镇人均食品水足迹影响的模拟结果 |
| Table 5 Simulation results of impacts of urban residential income and food price on food water footprints per capita |
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| 地区 | 水足迹类型 | 模拟1 | 模拟2 | 模拟3 | 模拟4 | | 变化量/m³ | 变化比/% | 变化量/m³ | 变化比/% | 变化量/m³ | 变化比/% | 模拟值/m³ | 实际值/m³ | | 东北部 | 总水足迹 | 34.7 | 7.1 | -10.9 | -2.2 | 23.8 | 4.9 | 590.2 | 628.0 | | 绿水 | 25.9 | 6.9 | -7.5 | -2.0 | 18.4 | 4.9 | 451.1 | 485.7 | | 蓝水 | 2.4 | 9.0 | -0.7 | -2.5 | 1.7 | 6.5 | 31.7 | 35.2 | | 灰水 | 6.4 | 7.4 | -2.7 | -3.1 | 3.7 | 4.3 | 107.4 | 107.1 | | 东部 | 总水足迹 | 31.8 | 6.7 | -11.1 | -2.3 | 20.7 | 4.4 | 605.9 | 605.6 | | 绿水 | 24.2 | 6.5 | -7.8 | -2.1 | 16.4 | 4.4 | 461.5 | 464.7 | | 蓝水 | 2.0 | 8.1 | -0.8 | -2.2 | 1.2 | 5.9 | 40.9 | 40.1 | | 灰水 | 5.6 | 7.0 | -2.5 | -3.4 | 3.1 | 3.6 | 103.5 | 100.8 | | 中部 | 总水足迹 | 34.4 | 7.3 | -8.8 | -1.9 | 25.6 | 5.4 | 587.5 | 553.9 | | 绿水 | 25.8 | 7.0 | -6.0 | -1.7 | 19.8 | 5.3 | 453.2 | 429.2 | | 蓝水 | 2.4 | 9.5 | -0.5 | -1.9 | 1.9 | 7.6 | 31.3 | 31.7 | | 灰水 | 6.2 | 7.6 | -2.3 | -2.8 | 3.9 | 4.8 | 103.0 | 92.9 | | 西部 | 总水足迹 | 35.7 | 7.5 | -9.8 | -2.1 | 25.9 | 5.4 | 585.5 | 582.3 | | 绿水 | 26.3 | 7.3 | -6.8 | -1.9 | 19.5 | 5.4 | 453.1 | 456.7 | | 蓝水 | 2.2 | 9.7 | -0.6 | -2.4 | 1.6 | 7.3 | 31.7 | 30.1 | | 灰水 | 7.2 | 7.9 | -2.4 | -3.1 | 4.8 | 4.8 | 100.7 | 95.5 |
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