稻虾共作模式碳足迹评价的敏感性和不确定性分析

Sensitivity and uncertainty analysis of carbon footprint evaluation: A case study of rice-crayfish coculture in China

  • 摘要: 客观全面地评价稻虾共作模式的碳足迹对于稻田综合种养产业的低碳绿色发展具有重要意义。对碳足迹进行敏感性和不确定性分析有助于增加评价结果的稳健性, 并为未来进一步优化参数和降低评价结果的不确定性提供借鉴。本研究基于大田试验和生命周期评价方法(LCA), 以单位面积、单位产值和单位营养密度单元(NDU)为功能单位对水稻单作和稻虾共作模式进行较为全面的碳足迹评价。结果表明, 水稻单作和稻虾共作模式的单位面积碳足迹分别为14 126 kg(CO2-eq)∙hm–2和13 140 kg(CO2-eq)∙hm–2。由于稻虾共作有更高的经济产值和营养密度输出, 该模式的单位产值碳足迹0.11 kg(CO2-eq)∙¥–1和单位NDU碳足迹3.05 kg(CO2-eq)∙NDU–1分别比水稻单作降低81.4%和49.3%, 而该模式的净生态系统经济预算(85 745 ¥∙hm–2)比水稻单作增加511.5%。热点分析表明, CH4排放(59.8%)、电力消耗(13.8%)和饲料投入(12.3%)对稻虾共作模式的碳足迹构成贡献较大, 这几个参数比其他输入参数对评价结果的影响程度也更大。不确定性分析表明, 在95%的置信区间下, 稻虾共作模式的单位面积碳足迹为11 179~15 613 kg(CO2-eq)∙hm–2。本研究结果突显了稻虾共作模式丰富的营养产出功能, 并从改善居民饮食结构的角度剖析了传统农业向生态农业转型的迫切性和必要性。本研究所使用的方法可为具有多功能产出的农业生产系统进行更全面的碳足迹评价提供技术支撑。

     

    Abstract: Rice-crayfish coculture has recently been developed owing to its high economic benefits. In 2020, the area used for rice-crayfish coculture in China reached 1.26×106 hm2. The objective and comprehensive evaluation of the carbon footprint of rice-crayfish coculture is crucial for low-carbon green development of the integrated farming industry of rice and aquaculture animals. Sensitivity and uncertainty analyses of carbon footprint can help to increase the robustness of the evaluation results and provide a reference to further optimize parameters and reduce the uncertainty of evaluation results in the future. Based on a field experiment and life cycle assessment (LCA), a comprehensive carbon footprint evaluation of rice monoculture and rice-crayfish coculture was carried out using 1 hm2 (area), 1 ¥ (output value), and 1 NDU (nutrient density unit) as the functional units (FU). The results showed that the carbon footprint per hectare (CFA) of rice monoculture and rice-crayfish coculture was 14 126 kg(CO2-eq)·hm–2 and 13 140 kg(CO2-eq)·hm–2, respectively; the latter was 7.0% lower than the former. Compared with rice monoculture, rice-crayfish coculture had higher economic output value and nutrition density delivery. Thus, the carbon footprint per output value 0.11 kg(CO2-eq)·¥–1 and carbon footprint per NDU 3.05 kg(CO2-eq)·NDU–1 of rice-crayfish coculture was 49.3%–81.4% lower than those of rice monoculture, whereas the net ecosystem economic budget (NEEB) of rice-crayfish coculture (85 745 ¥·hm–2) was 511.5% higher than that of rice monoculture. Hotspot analysis showed that CH4 emissions, electricity consumption, and feed input contributed greatly to carbon footprint, accounting for 59.8%, 13.8%, and 12.3%, respectively. The application of urea, compound fertilizer, and organic fertilizer contributed 4.7%, 3.8%, and 1.5% to carbon footprint, respectively; and N2O emissions, diesel consumption, and rice seeds contributed even less (3.3%, 0.3%, and 0.4%, respectively). Sensitivity analysis showed that the carbon footprint was most sensitive to CH4 emissions. When CH4 emissions varied by ±40%, the carbon footprint varied between 9994 and 16 283 kg(CO2-eq)·hm–2. Carbon footprint was also sensitive to electricity consumption and feed input. When these two parameters were varied by ±40%, the carbon footprint varied from 12 413 to 13 864 kg(CO2-eq)·hm–2 and 12 491 to 13 787 kg(CO2-eq)·hm–2, respectively. Other parameters (i.e., diesel consumption, organic fertilizer, and rice seed inputs) had a weaker impact on the carbon footprint. The results of uncertainty analysis showed that the mean value of the carbon footprint of rice-crayfish coculture was 13 302±1166 kg(CO2-eq)∙hm–2, and the median and coefficient of variation were 13 250 kg(CO2-eq)·hm–2 and 8.76%, respectively, indicating a weak variation. Under 95% confidence interval, the CFA of rice-crayfish coculture varied between 11 179 and 15 613 kg(CO2-eq)·hm–2. The results of this study highlighted the rich nutritional output function of rice-crayfish coculture and analyzed the urgency and necessity of transforming traditional agriculture to ecological agriculture from the perspective of improving the dietary structure of residents. The methods used in this study can provide technical support for a more comprehensive carbon footprint evaluation of agricultural production systems with multi-functional outputs.

     

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