基于两种LCA方法学的奶牛集约化和牧户养殖环境影响分析

Rapid increasing demands for dairy products in China calls for an urgent action to balance the consumptions and environmental impacts. Life Cycle Assessment (LCA) is among the most promising approach to address this knowledge need because it is considered as a holistic assessment of multiple environmental impacts. Yet, arbitrary selection of attributional LCA (ALCA) or consequential LCA (CLCA), coupled with various technical challenges, post extreme challenges in identifying environmentally-friendly ways for effective dairy production systems (i.e. intensive vs. pastoralism system). Key challenges include an appropriate definition of the functional unit (FU) and choices of allocation methods, recognition of methods for addressing and modeling indirect impacts, and identification of key contributing factors at management level and system-scale. Our objective hence is set to: 1) distinguish the key characteristics and applicability of ALCA and CLCA for dairy farming systems; 2) develop a method for modeling the spatiotemporal dynamics of the indirect impacts on the environment; 3) assess the sensitivity of key technical factors (i.e. FU and allocation methods); and 4) identify leading factors contributing to environmental performance from both process level and system-scale. Our objectives will be achieved by using the intensively managed dairy farming systems in Inner Mongolia as our testbed, applying ALCA and CLCA to quantify the direct and indirect environmental performances of the contrasting systems. We aim at both theoretical advancement and practical applications of the LCA methods for the dairy farming systems, which will: 1) lead LCA methodology development of livestock systems in grassland pastoral regions of China; 2) explore the integration of simulation models to establish a temporally- and spatially-dynamic LCI for studies on the indirect environmental impacts in complex systems such as livestock production; 3) provide practical protocols and models on sensitivity of FU and allocation methods to further understand the key issues facing the LCA scholars; and 4) pioneer the use of emerging statistical analysis for other relevant Chinese studies in identifying the underlying mechanisms and mitigation schemes for livestock production system from both process and system perspectives.

我国对乳制品需求的激增，要求有效的评估方法来量化畜牧生产的环境影响。生命周期评价方法（LCA）是解决这一难题最优方法之一。然而如何选择归因（ALCA）或归果LCA（CLCA），加上多方面技术挑战，导致目前尚无法准确量化不同畜牧生产系统（如集约化或牧户养殖）的环境影响。项目旨在区分ALCA和CLCA的关键特征及适用性，开发量化间接环境影响的时空动态LCA模型，识别关键技术因素（如功能单位和分配方法）的敏感性，同时在生产过程和系统层面上提取导致环境影响的主要因素。我们将以内蒙古谢尔塔拉牧场为调研基地，通过ALCA和CLCA来量化集约化和牧户养殖的直接和间接环境影响。该研究从过程和系统层面上寻求畜牧生产对环境的调节机制和缓解方案；通过整合模拟模型，建立时空动态LCA，为研究畜牧生产等复杂系统的环境影响提供坚实例案；通过解决关键技术难题，为今后LCA在相关领域的拓展应用提供具体方案。

本次项目为厘清呼伦贝尔草原生态系统不同放牧生产活动的环境影响，开发并应用不同生命周期环境影响评估（LCA）模型。其中，通过归因/归果LCA（ALCA/CLCA）对比了不同生产体系，即散户养殖模式，集约生产系统，以及过渡生产系统。结果显示散户养殖模式具有较低的生产效率及单位产品较高的环境影响，若要更换当前的散户养殖模式，当纳入间接影响后，过渡生产系统的CLCA结果显示出不同于ALCA结果的环境影响模式。可用替代的减排计划在于控制直接排放，提高其生产效率和能源结构。同时，通过摇篮到大门的空间化LCA对所选呼伦贝尔草原畜牧业活动的环境影响进行评估，并结合空间统计数据，发现靠近海拉尔市的牧场具有高排放特征，而位于海拉尔市南/西部的牧场则具有低排放特征。结果发现现场直接动物排放在清单阶段没有表现出空间依赖性，但其产生的LCA影响分数显示了较强的空间依赖性，这取决于在生命周期影响评估阶段是否以及如何引入评估模型的空间位置及分辨率。以上不同LCA模型结果均揭露在不同环境影响类别之间发生环境负担转移，这佐证在2060碳中和目标的目标前提下，政策决策者应通过综合考量环境影响，以提高畜牧业系统的生产效率为目标制定科学的减排政策。