Using Activity‐Based Modeling to Simulate Urban Resource Demands at High Spatial and Temporal Resolutions

摘要: Summary Urban metabolism is an important technique for understanding the relationship between cities and wider environment. Such analyses are typically performed at scale of whole city using annual average data, a feature that driven largely by restrictions in data availability. However, order to assess resource implications policy interventions design operate efficient urban infrastructures such as energy systems, greater spatial temporal resolutions required underlying demand data. As this information rarely available, we propose these profiles might be simulated activity-based modeling. This microsimulation approach calculates activity schedules individuals within then converts into demands. The method demonstrated simulating electricity natural gas demands London examining how nontransport change response shift commuting patterns, example, congestion charge or similar policy. article concludes discussing strengths weaknesses approach, well highlighting future research directions. Key challenges include simulation in-home activities, assessing transferability complex sets models supporting analyses, determining which aspects would benefit most from technique.