Urbanization is reshaping China's economy, society, and energy system. Between 1990 and 2008 China added more than 300 million new urban residents, bringing the total urbanization rate to 46%. The ongoing population shift is spurring energy demand for new construction, as well as additional residential use with the replacement of rural biomass by urban commercial energy services. This project developed a modeling tool to quantify the full energy consequences of a particular form of urban residential development in order to identify energy- and carbon-efficient modes of neighborhood-level development and help mitigate resource and environmental implications of swelling cities.
LBNL developed an integrated modeling tool that combines process-based lifecycle assessment with agent-based building operational energy use, personal transport, and consumption modeling. The lifecycle assessment approach was used to quantify energy and carbon emissions embodied in building materials production, construction, maintenance, and demolition. To provide more comprehensive analysis, LBNL developed an agent-based model as described below. The model was applied to LuJing, a residential development in Jinan, Shandong Province, to provide a case study and model proof of concept.
This study produced results data that are unique by virtue of their scale, scope and type. Whereas most existing literature focuses on building-, city-, or national-level analysis, this study covers multi-building neighborhood-scale development. Likewise, while most existing studies focus exclusively on building operational energy use, this study also includes embodied energy related to personal consumption and buildings. Within the boundaries of this analysis, food is the single largest category of the building energy footprint, accounting for 23% of the total.
On a policy level, the LCA approach can be useful for quantifying the energy and environmental benefits of longer average building lifespans. In addition to prospective analysis for standards and certification,urban form modeling can also be useful in calculating or verifying ex post facto, bottom-up carbon emissions inventories. Emissions inventories provide a benchmark for evaluating future outcomes and scenarios as well as an empirical basis for valuing low-carbon technologies. By highlighting the embodied energy and emissions of building materials, the LCA approach can also be used to identify the most intensive aspects of industrial production and the supply chain. The agent based modeling aspect of the model can be useful for understanding how policy incentives can impact individual behavior andthe aggregate effects thereof.
The most useful elaboration of the urban form assessment model would be to further generalize it for comparative analysis. Scenario analysis could be used for benchmarking and identification of policy priorities. If the model is to be used for inventories, it is important to disaggregate the energy use data for more accurate emissions modeling. Depending on the policy integration of the model, it may be useful to incorporate occupancy data for per-capita results. On the question of density and efficiency, it may also be useful to integrate a more explicit spatial scaling mechanism for modeling neighborhood and city-level energy use and emissions, i.e. to account for scaling effects in public infrastructure and transportation.