Introduction: When modelling complex systems such as cities, a quality-complexity compromise is to subdivide them into smaller cells. Life Cycle Assessment can help to comprehensively handle urban intricacies but is a data-intensive technique. Balancing data requirement and collection feasibility while acknowledging uncertainty become key. Methods: This research explored top-down and bottom-up approaches to generate information input for environmental modelling at neighbourhood scale and to identify strategies to improve modelling while balancing data collection needs. SimaPro v.9 supported the assessments. Results: Influence of elements like interior finishings and wall partitions is not captured by the top-down approach, but should not be neglected, for their impacts are substantial. Modelling can be improved by application of cut-off rules to limit data requirements and cluster sampling techniques to derive a minimum range of archetypes to adequately describe the studied area. Finally, an evolutive hybrid approach is suggested to gradually improve both background archetypes and foreground bottom-up objects.

简介：在对诸如城市之类的复杂系统进行建模时，质量复杂性的折衷是将它们细分为较小的单元。生命周期评估可以帮助全面处理城市复杂性，但这是一项数据密集型技术。在确认不确定性的同时，平衡数据需求和收集可行性成为关键。方法：本研究探索了自上而下和自下而上的方法，以在邻域范围内为环境建模生成信息输入，并确定在平衡数据收集需求的同时改善建模的策略。SimaPro v.9支持评估。结果：自上而下的方法无法捕捉到诸如室内装饰和墙隔断之类的元素的影响，但由于其影响很大，因此不应忽略。可以通过应用截断规则来限制数据需求，并使用聚类采样技术来导出原型的最小范围以充分描述研究区域，从而改进建模。最后，提出了一种渐进的混合方法来逐渐改善背景原型和前景自下而上的对象。