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伊朗吉兰省传统和综合水稻农场的生命周期评估和模糊建模评价。

Evaluation of traditional and consolidated rice farms in Guilan Province, Iran, using life cycle assessment and fuzzy modeling.

机构信息

Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.

Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran.

出版信息

Sci Total Environ. 2014 May 15;481:242-51. doi: 10.1016/j.scitotenv.2014.02.052. Epub 2014 Mar 3.

Abstract

In this study the environmental impact of consolidated rice farms (CF) - farms which have been integrated to increase the mechanization index - and traditional farms (TF) - small farms with lower mechanization index - in Guilan Province, Iran, were evaluated and compared using Life cycle assessment (LCA) methodology and adaptive neuro-fuzzy inference system (ANFIS). Foreground data were collected from farmers using face-to-face questionnaires and background information about production process and inventory data was taken from the EcoInvent®2.0 database. The system boundary was confined to within the farm gate (cradle to farm gate) and two functional units (land and mass based) were chosen. The study also included a comparison of the input-output energy flows of the farms. The results revealed that the average amount of energy consumed by the CFs was 57 GJ compared to 74.2 GJ for the TFs. The energy ratios for CFs and TFs were 1.6 and 0.9, respectively. The LCA results indicated that CFs produced fewer environmental burdens per ton of produced rice. When compared according to the land-based FU the same results were obtained. This indicates that the differences between the two types of farms were not caused by a difference in their production level, but rather by improved management on the CFs. The analysis also showed that electricity accounted for the greatest share of the impact for both types of farms, followed by P-based and N-based chemical fertilizers. These findings suggest that the CFs had superior overall environmental performance compared to the TFs in the study area. The performance metrics of the model based on ANFIS show that it can be used to predict the environmental burdens of rice production with high accuracy and minimal error.

摘要

本研究采用生命周期评价(LCA)方法和自适应神经模糊推理系统(ANFIS)对伊朗吉兰省整合提高机械化指数的集约水稻农场(CF)和机械化指数较低的小型传统农场(TF)的环境影响进行了评价和比较。通过面对面的问卷调查收集了农场主的原始数据,从 EcoInvent®2.0 数据库中获取了有关生产过程和清单数据的背景信息。系统边界限定在农场内部(摇篮到农场门),选择了两个功能单元(土地和质量)。该研究还包括对农场投入产出能量流的比较。结果表明,CF 的平均能源消耗为 57 GJ,而 TF 为 74.2 GJ。CF 和 TF 的能源比分别为 1.6 和 0.9。LCA 结果表明,每生产一吨水稻,CF 产生的环境负担较少。根据基于土地的 FU 进行比较,也得到了相同的结果。这表明两种类型的农场之间的差异不是由其生产水平的差异引起的,而是由于 CF 管理的改善。分析还表明,电力占两种类型农场影响的最大份额,其次是基于 P 和 N 的化学肥料。这些发现表明,在研究区域,CF 相对于 TF 具有更好的整体环境性能。基于 ANFIS 的模型的性能指标表明,它可以用于以高精度和最小误差预测水稻生产的环境负担。

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