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Abstract：
UNASSIGNED: The study\'s objective is to assess the environmental performance of rice production in Northern Italy, in particular in Piedmont, the first Italian and European district for the rice-growing area, and thus identify the most critical hotspots and agricultural processes. In particular, as a case study, a farm located in Vercelli (VC) has been chosen. Subsequently, the study results were compared with other different cultivation practices to evaluate the most sustainable choice.
UNASSIGNED: The application of the LCA has been performed, highlighting the phases of rice production that have the most significant impact. Then, uncertainty and sensitivity analyses have been made to estimate the robustness of the results and assess the influence of changing some input variables on emission reduction. Finally, multivariate statistical, specifically a principal component analysis (PCA), was conducted to aid the interpretation of the output dataset of this case study. LCA, uncertainty analysis, and sensitivity analysis were performed with SimaPro 9.2.0, using ReCiPe 2016 Midpoint (H) methodology, and PCA with R software.
UNASSIGNED: The hotspot with the highest environmental load is irrigation, which compared to the other phases impacts more in 15 out of 18 categories, including 12 with impacts greater than + 75%. This is because irrigation causes direct impacts, related to the methanogenesis in rice fields, but also indirect impacts related mainly to the production of the energy mix required to move the large masses of irrigation water. Therefore, different water management systems were compared and results show that the irrigation systems based on intermittent paddy submergence (DSI) could result in - 40% lower impacts, resulting to be the preferable technique over the other irrigation systems analyzed, including the traditional one used in this study.
UNASSIGNED: In order to reduce the environmental impacts related to the irrigation process, a water management system characterized by intermittent flooding of the paddy field (DSI) could be used as it reduces the environmental impacts the most (- 40%), while the least suitable system is one characterized by continuous flooding without drought periods, as it causes the highest impacts.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s11367-022-02109-x.
UNASSIGNED: The application of the LCA has been performed, highlighting the phases of rice production that have the most significant impact. Then, uncertainty and sensitivity analyses have been made to estimate the robustness of the results and assess the influence of changing some input variables on emission reduction. Finally, multivariate statistical, specifically a principal component analysis (PCA), was conducted to aid the interpretation of the output dataset of this case study. LCA, uncertainty analysis, and sensitivity analysis were performed with SimaPro 9.2.0, using ReCiPe 2016 Midpoint (H) methodology, and PCA with R software.
UNASSIGNED: The hotspot with the highest environmental load is irrigation, which compared to the other phases impacts more in 15 out of 18 categories, including 12 with impacts greater than + 75%. This is because irrigation causes direct impacts, related to the methanogenesis in rice fields, but also indirect impacts related mainly to the production of the energy mix required to move the large masses of irrigation water. Therefore, different water management systems were compared and results show that the irrigation systems based on intermittent paddy submergence (DSI) could result in - 40% lower impacts, resulting to be the preferable technique over the other irrigation systems analyzed, including the traditional one used in this study.
UNASSIGNED: In order to reduce the environmental impacts related to the irrigation process, a water management system characterized by intermittent flooding of the paddy field (DSI) could be used as it reduces the environmental impacts the most (- 40%), while the least suitable system is one characterized by continuous flooding without drought periods, as it causes the highest impacts.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s11367-022-02109-x.
摘要：
UNASSIGNED：该研究的目的是评估意大利北部稻米生产的环境绩效，特别是在皮埃蒙特,第一个意大利和欧洲水稻种植区，从而确定最关键的热点和农业过程。特别是,作为一个案例研究，已选择位于Vercelli（VC）的农场。随后，将研究结果与其他不同种植方法进行比较，以评估最可持续的选择。
UNASSIGNED：已执行LCA的应用程序，突出水稻生产的阶段，具有最显著的影响。然后，进行了不确定性和敏感性分析，以估计结果的稳健性，并评估改变一些输入变量对减排的影响。最后,多元统计，特别是主成分分析(PCA)，进行是为了帮助解释本案例研究的输出数据集。LCA,不确定性分析，并使用SimaPro9.2.0进行敏感性分析，使用ReCiPe2016中点(H)方法，和PCA与R软件。
UNASSIGNED：环境负荷最高的热点是灌溉，与其他阶段相比，18个类别中的15个影响更大，包括影响大于+75%的12个。这是因为灌溉会造成直接影响，与稻田产甲烷有关，但间接影响主要与移动大量灌溉水所需的能源组合的生产有关。因此,比较了不同的水管理系统，结果表明，基于间歇性稻田淹没（DSI）的灌溉系统可以降低-40％的影响，结果是比分析的其他灌溉系统更可取的技术，包括本研究中使用的传统方法。
UNASSIGNED：为了减少与灌溉过程有关的环境影响，可以使用以稻田间歇性洪水（DSI）为特征的水管理系统，因为它最大程度地减少了对环境的影响（-40％），虽然最不合适的系统是一个以持续洪水而没有干旱期为特征的系统，因为它造成了最大的影响。
UNASSIGNED：在线版本包含补充材料，可在10.1007/s11367-022-02109-x获得。
UNASSIGNED：已执行LCA的应用程序，突出水稻生产的阶段，具有最显著的影响。然后，进行了不确定性和敏感性分析，以估计结果的稳健性，并评估改变一些输入变量对减排的影响。最后,多元统计，特别是主成分分析(PCA)，进行是为了帮助解释本案例研究的输出数据集。LCA,不确定性分析，并使用SimaPro9.2.0进行敏感性分析，使用ReCiPe2016中点(H)方法，和PCA与R软件。
UNASSIGNED：环境负荷最高的热点是灌溉，与其他阶段相比，18个类别中的15个影响更大，包括影响大于+75%的12个。这是因为灌溉会造成直接影响，与稻田产甲烷有关，但间接影响主要与移动大量灌溉水所需的能源组合的生产有关。因此,比较了不同的水管理系统，结果表明，基于间歇性稻田淹没（DSI）的灌溉系统可以降低-40％的影响，结果是比分析的其他灌溉系统更可取的技术，包括本研究中使用的传统方法。
UNASSIGNED：为了减少与灌溉过程有关的环境影响，可以使用以稻田间歇性洪水（DSI）为特征的水管理系统，因为它最大程度地减少了对环境的影响（-40％），虽然最不合适的系统是一个以持续洪水而没有干旱期为特征的系统，因为它造成了最大的影响。
UNASSIGNED：在线版本包含补充材料，可在10.1007/s11367-022-02109-x获得。
