HR: 1330h
AN: B42A-0936    [PDF]
TI: A Method for Improving Temporal and Spatial Resolution of Carbon Dioxide Emissions
AU: * Gregg, J S
EM: jay.gregg@und.nodak.edu
AF: University of North Dakota, Department of Space Studies, Grand Forks, ND 58202-9008 United States
AU: Andres, R J
EM: andres@space.edu
AF: University of North Dakota, Department of Space Studies, Grand Forks, ND 58202-9008 United States
AB: Using United States data, a method is developed to estimate the monthly consumption of solid, liquid and gaseous fossil fuels for each state in the union. This technique employs monthly sales data to estimate the relative monthly proportions of the total annual national fossil fuel use. These proportions are then used to estimate the total monthly carbon dioxide emissions for each state. To assess the success of this technique, the results from this method are compared with the data obtained from other independent methods. To determine the temporal success of the method, the resulting national time series is compared to the model produced by Carbon Dioxide Information Analysis Center (CDIAC) and the current model being developed by T. J. Blasing and C. Broniak at the Oak Ridge National Laboratory (ORNL). The University of North Dakota (UND) method fits well temporally with the results of the CDIAC and current ORNL research. To determine the success of the spatial component, the individual state results are compared to the annual state totals calculated by ORNL. Using ordinary least squares regression, the annual state totals of this method are plotted against the ORNL data. This allows a direct comparison of estimates in the form of ordered pairs against a one-to-one ideal correspondence line, and allows for easy detection of outliers in the results obtained by this estimation method. Analyzing the residuals of the linear regression model for each type of fuel permits an improved understanding of the strengths and shortcomings of the spatial component of this estimation technique. Spatially, the model is successful when compared to the current ORNL research. The primary advantages of this method are its ease of implementation and universal applicability. In general, this technique compares favorably to more labor-intensive methods that rely on more detailed data. The more detailed data is generally not available for most countries in the world. The methodology used here will be applied to other nations in the world to better understand their sub-annual cycle and sub-national spatial distribution of carbon dioxide emissions from fossil fuel consumption. Better understanding of the cycle will lead to better models used for predicting and responding to global environmental changes currently observed and anticipated.
DE: 0322 Constituent sources and sinks
DE: 0330 Geochemical cycles
DE: 1600 GLOBAL CHANGE (New category)
DE: 1610 Atmosphere (0315, 0325)
DE: 1694 Instruments and techniques
SC: Biogeosciences [B]
MN: 2003 Fall Meeting