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Detailed estimates of carbon dioxide (CO 2 ) emissions at fine spatial scales are useful to both modelers and decision makers who are faced with the problem of global warming and climate change. Globally, transport related emissions of carbon dioxide are growing. This letter presents a new method based on the volume-preserving principle in the areal interpolation literature to disaggregate transportation-related CO 2 emission estimates from the county-level scale to a 1 km 2 grid scale. The proposed volume-preserving interpolation (VPI) method, together with the distance-decay principle, were used to derive emission weights for each grid based on its proximity to highways, roads, railroads, waterways, and airports. The total CO 2 emission value summed from the grids within a county is made to be equal to the original county-level estimate, thus enforcing the volume-preserving property. The method was applied to downscale the transportation-related CO 2 emission values by county (i.e. parish) for the state of Louisiana into 1 km 2 grids. The results reveal a more realistic spatial pattern of CO 2 emission from transportation, which can be used to identify the emission 'hot spots'. Of the four highest transportation-related CO 2 emission hotspots in Louisiana, high-emission grids literally covered the entire East Baton Rouge Parish and Orleans Parish, whereas CO 2 emission in Jefferson Parish (New Orleans suburb) and Caddo Parish (city of Shreveport) were more unevenly distributed. We argue that the new method is sound in principle, flexible in practice, and the resultant estimates are more accurate than previous gridding approaches.

A new method for estimating carbon dioxide emissions from transportation at fine spatial scales