Measuring greenhouse gas emissions from cities
Event details
| Date | 06.11.2012 |
| Hour | 16:15 › 17:15 |
| Speaker |
Prof. Andreas Christen, Department of Geography / Atmospheric Science Program, University of British Columbia, Canada |
| Location | |
| Category | Conferences - Seminars |
A reduction of anthropogenic greenhouse gas emissions (GHG) is on the agenda of many governments and unsurprisingly cities are a focus for emission reduction efforts. To reduce GHG emissions in cities, several approaches are discussed and implemented. Those include switches in the energy supply systems, changes in technology and more broadly sustainable urban planning and design strategies (e.g. land-use-mix, density, vegetation). Such strategies must be informed and guided by rigorous scientific evidence and simulations.
This ENAC seminar will present how modeled GHG emissions from an entire urban ecosystem (including emissions from traffic, buildings, diffuse sources, soils and uptake by vegetation) can be validated against or informed by direct flux measurements in the atmosphere above an urban area. We will focus on GHG flux measurements using eddy-covariance (EC) systems on fixed micrometeorological towers although aerial platforms would be also possible. In particular, the seminar talk will explain how emission factors of carbon-dioxide (CO2) and methane (CH4) can be constrained by a statistical analysis of long-term EC flux measurements, if the location and behavior of the emission source are known but their magnitude is not. This is achieved by combining EC flux measurements with a backward dispersion model and a geographic information system (GIS) of the known location of emission sources.
To demonstrate the potential and limitations of the EC approach, we will use data from a relatively uniform 4 km2 residential neighborhood in Vancouver, BC, Canada with about 6’000 detached houses and 23’000 inhabitants. The neighborhood, called ‘Vancouver-Sunset’ offers a long-term dataset of continuous GHG flux measurements of CO2, and CH4 on top of a 30m research tower. The urban ecosystem surrounding the tower has been characterized by a combination of urban object classifications (buildings, trees, land-cover) automatically derived from Light Detection and Ranging (LiDAR) and optical remote sensing data. Further, spatial census data, assessment data, traffic counts, building energy models, and measured soil and vegetation models determine the location of emission (and uptake) processes and their expected magnitude over time. Modeled GHG emissions in a GIS and directly measured GHG fluxes are brought in agreement using a backward-dispersion model (source area model) to attribute measured fluxes to a given weighted spatial subset of the urban surface. This attribution is repeated for many time steps with changing source area configuration (wind direction) and temporal characteristics of emissions (day-night, weekday-weekend, summer-winter) - which allows a statistical optimization / attribution of emission factors to GHG sources of known location but unknown intensity.
The presented results demonstrate that direct GHG flux measurements based on the EC approach - if sites are carefully chosen - are a promising approach to validate fine-scale urban emission inventories/models and can inform emission factors under realistic conditions. EC flux measurements fill a gap on GHG emission data at intermediate urban scales - between known emissions of selected elements of an urban system (cars, space heating systems, individual buildings) and data assimilation modeling using atmospheric concentration measurements on regional to continental scales.
This ENAC seminar will present how modeled GHG emissions from an entire urban ecosystem (including emissions from traffic, buildings, diffuse sources, soils and uptake by vegetation) can be validated against or informed by direct flux measurements in the atmosphere above an urban area. We will focus on GHG flux measurements using eddy-covariance (EC) systems on fixed micrometeorological towers although aerial platforms would be also possible. In particular, the seminar talk will explain how emission factors of carbon-dioxide (CO2) and methane (CH4) can be constrained by a statistical analysis of long-term EC flux measurements, if the location and behavior of the emission source are known but their magnitude is not. This is achieved by combining EC flux measurements with a backward dispersion model and a geographic information system (GIS) of the known location of emission sources.
To demonstrate the potential and limitations of the EC approach, we will use data from a relatively uniform 4 km2 residential neighborhood in Vancouver, BC, Canada with about 6’000 detached houses and 23’000 inhabitants. The neighborhood, called ‘Vancouver-Sunset’ offers a long-term dataset of continuous GHG flux measurements of CO2, and CH4 on top of a 30m research tower. The urban ecosystem surrounding the tower has been characterized by a combination of urban object classifications (buildings, trees, land-cover) automatically derived from Light Detection and Ranging (LiDAR) and optical remote sensing data. Further, spatial census data, assessment data, traffic counts, building energy models, and measured soil and vegetation models determine the location of emission (and uptake) processes and their expected magnitude over time. Modeled GHG emissions in a GIS and directly measured GHG fluxes are brought in agreement using a backward-dispersion model (source area model) to attribute measured fluxes to a given weighted spatial subset of the urban surface. This attribution is repeated for many time steps with changing source area configuration (wind direction) and temporal characteristics of emissions (day-night, weekday-weekend, summer-winter) - which allows a statistical optimization / attribution of emission factors to GHG sources of known location but unknown intensity.
The presented results demonstrate that direct GHG flux measurements based on the EC approach - if sites are carefully chosen - are a promising approach to validate fine-scale urban emission inventories/models and can inform emission factors under realistic conditions. EC flux measurements fill a gap on GHG emission data at intermediate urban scales - between known emissions of selected elements of an urban system (cars, space heating systems, individual buildings) and data assimilation modeling using atmospheric concentration measurements on regional to continental scales.
Practical information
- General public
- Free
- This event is internal
Organizer
- IIE
Contact
- Prof. Marc Parlange, EFLUM