Thursday, October 11, 2012
Resarchers from Arizona State have created a program that maps CO2 in cities. What is fascinating about this project is that they can map it down to the level of individual blocks and buildings. While this program is only currently focused on urban areas, global CO2 maps (and particularly maps of rural areas) could be pivotal in any programs related to carbon emissions. It could enable us to identify the heaviest producers and also perhaps assist in sequestration programs. They even made a cool video showing how it works. What a great tool for local governments.
Here is the citation and abstract:
Kevin R. Gurney, Igor Razlivanov, Yang Song, Yuyu Zhou, Bedrich Benes, & Michel Abdul-Massih, Quantification of Fossil Fuel CO2 Emissions on the Building/Street Scale for a Large U.S. City, Envtl Sci. & Tech. (August 15, 2012)
In order to advance the scientific understanding of carbon exchange with the land surface, build an effective carbon monitoring system, and contribute to quantitatively based U.S. climate change policy interests, fine spatial and temporal quantification of fossil fuel CO2 emissions, the primary greenhouse gas, is essential. Called the “Hestia Project”, this research effort is the first to use bottom-up methods to quantify all fossil fuel CO2 emissions down to the scale of individual buildings, road segments, and industrial/electricity production facilities on an hourly basis for an entire urban landscape. Here, we describe the methods used to quantify the on-site fossil fuel CO2 emissions across the city of Indianapolis, IN. This effort combines a series of data sets and simulation tools such as a building energy simulation model, traffic data, power production reporting, and local air pollution reporting. The system is general enough to be applied to any large U.S. city and holds tremendous potential as a key component of a carbon-monitoring system in addition to enabling efficient greenhouse gas mitigation and planning. We compare the natural gas component of our fossil fuel CO2 emissions estimate to consumption data provided by the local gas utility. At the zip code level, we achieve a bias-adjusted Pearson r correlation value of 0.92 (p < 0.001).
- Jessie Owley
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