A LiDAR-based urban metabolism approach to neighbourhood scale energy and carbon emissions modelling
Creators: name: Christen, Andreas
name: Coops, Nicholas C.
name: Kellett, Ronald
name: Crawford, Ben
name: Heyman, Eli
name: Olchovski, Inna
name: Tooke, Thoreau Rory
name: Van Der Laan, Michael Tije
Publisher: name: University of British Columbia
Year: 2012

description: [Research report published as hard copy (UBC)] A LIDAR-BASED URBAN METABOLISM APPROACH TO NEIGHBOURHOOD SCALE ENERGY AND CARBON EMISSIONS MODELLING prototypes a remote sensingbased means to neighbourhood-scale energy and carbon modelling. Building on a Vancouver case study neighbourhood for which remote sensing, atmospheric carbon flux, urban form, energy and emissions data have been compiled and aggregated, the project demonstrates a replicable neighbourhood-scale approach that illustrates: • Holistic, systems-based and context-sensitive approaches to urban energy and carbon emissions modelling. • Methods of deriving energy- and emissionsrelated urban form attributes (land use, building type, vegetation, for example) from 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, type-based methods of building energy modeling and scenario-building. • Benchmark comparisons of modelled estimates with directly measured energy consumption data and two years of directly measured carbon fluxes (emissions) on a research tower above the neighbourhood. 0.0.1 Key Model Results • Carbon imports: Based on project urban metabolism scope and methods, the study area imports approximately 6.69 kg C m⁻² year⁻¹ (or 1.04 t C cap⁻¹) in form of fuels, food and materials and uptakes 0.49 kg C m⁻² year⁻¹ from the atmosphere though photosynthesis of urban vegetation. • Carbon exports and sequestration: Sources within the study area emit 6.22 kg C m⁻² year⁻¹ (0.97 t C cap⁻¹) or 87% of the imports to the atmosphere, and 0.87 kg C m⁻² year⁻¹ (0.14 t C cap⁻¹) or 12% of the imports are exported laterally by waste. 1% of the imported carbon, or 0.09 kg C m⁻² year⁻¹ (0.01 t C cap⁻¹) is sequestered in urban soils and biomass. • Relevant emission processes: Out of all local emissions from the study area to the atmosphere, 2.47 kg C m⁻² year⁻¹ (40%) are originating from buildings, 2.93 kg C m⁻² year⁻¹ (47%) from transportation, 0.49 kg C m⁻² year⁻¹ (8%) from human respiration and 0.33 kg C m⁻² year⁻¹ (5%) from respiration of soils and vegetation. Emissions attributable to fuels, resource and food production, transport or transmission, and waste management outside the study neighborhood were not considered. • Fossil fuel emissions: Out of the local fossil fuel emissions in the study area, 46% originate from the building sector (natural gas), and 54% are attributable to transportation uses (gasoline, diesel). Out of the transportation emissions, 11% (0.31 kg C m⁻² year⁻¹) are attributable to carbon emitted on trips generated within the study area and 89% (2.62 kg C m⁻² year⁻¹) to carbon emitted on trips passing through the study area. • Renewable carbon cycling: Photosynthesis and human, soil and vegetation respiration take up / emit renewable carbon. These processes have potential to offset (take-up) carbon from other sources as well as generate (emit) carbon when carbon pools are disturbed, by urban land use change and (re-)development, for example. • Benchmark to direct emission measurements: Two years of measurements on a carbon flux tower in the centre of the study area allow a comparison of modelled results to directly measured carbon emissions. The modelled and measured emissions agreed very well i.e. 6.71 kg C m⁻² year⁻¹ were measured vs. 7.46 kg C m⁻² year⁻¹ modelled (refers to a subset of the study area weighted by the turbulent source are of the tower). The model is slightly overestimates actual emissions by 0.75 kg C m⁻² year⁻¹ (or 11%) which is mostly attributed to the lack of vehicle speed representation in the transportation model. 0.0.2 Key Findings on Project Methodology • Remote sensing: Remote sensing technologies such as LiDAR and multispectral satellite imagery have been demonstrated to be an effective means to generate, spatialize inputs and extract urban form and land cover data at fine scales (down to 1 m). These urban form attributes and data provide the inputs necessary to energy and emission modelling tasks in the building sector and to quantify vegetation emissions / uptake. • Building-type approach: Type-based modelling methods, data limitations aside, provide an effective means to scale building to neighbourhood energy modelling. These methods also facilitate definition of crucial morphological and performance attributes through which to filter remote sensing data and to scope potential mitigation strategies and scenarios. • Comparison of measured with modelled emissions: Direct carbon flux measurements on urban flux towers are demonstrated to be a method of validation of fine-scale emission inventories / models. Given the prototype nature of the approach and methods, close agreement between tower measurements and model results in this study is a successful and promising outcome. • Limitations: While promising, the urban metabolism approach demonstrated has also been necessarily limited in several ways. Only one metabolic aspect — mass balance of carbon, has been considered and measured. The spatial scale and complexity is modest — a 2km square ‘neighbourhood’ of moderate land use and urban form diversity. Out of study area carbon emissions generated in the production of food or consumer goods or the extent of local origin trips has not been considered. 0.0.3 Key Findings from Illustrative Scenarios • Material emissions reduction targets: Illustrative scenarios demonstrate that, on a per capita basis, local origin carbon emissions in the Sunset study area could meet British Columbia’s 2020 carbon reduction goal (33% below 2007 levels) with full adoption of current best practice space conditioning and vehicle fuel efficiency standards. However, progress toward greater emissions reductions beyond that goal require greater population and employment density in compact and mixed use, pedestrian- and transit-oriented patterns of urban form. Meeting British Columbia’s 2050 carbon reduction goal (80% below 2007 levels) would depend on full adoption of these best practice urban form strategies in combination with significant additional technological improvement in the energy efficiency of buildings, vehicles and infrastructure as well as significant human behaviour change toward less energy intensive lifestyles.