A LiDAR-based Urban Metabolism Approach to neighbourhood scale energy and carbon emissions modeling is used in estimating carbon emissions in a 2km square study area in Vancouver. A baseline carbon flow in the study area was measured from empirical data gathered at a carbon flux tower. Component carbon flows were spatially attributed to buildings, transportation, humans, food and waste, and vegetation and soils via remote sensing methods, utility and travel data. From this baseline, three urban form simulations illustrated the spatial implications of carbon emissions reductions targets.
- A holistic, systems-based and context-sensitive approach to urban carbon emissions modelling.
- Methods of deriving emissions-related urban form attributes (land use, building type, vegetation, for example) via remote sensing technologies.
- Methods of integrating diverse emission and uptake processes (combustion, respiration, photosynthesis), on a range of scales and resolutions based on spatial and non-spatial data relevant to urban form, energy and emissions modelling.
- Scalable, building type-based methods of building energy modeling and scenario-building.
- Benchmark comparisons of modelled estimates with measured energy consumption data.
- Findings that illuminate challenges of data, analysis and calibration in carbon emissions responsive planning and design at neighbourhood and greater scales.