摘要：Detailed estimates of carbon dioxide (CO2) 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
CO2 emission estimates from the county-level scale to a
1 km2 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
CO2 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
CO2 emission values by county (i.e. parish) for the state of Louisiana into
1 km2 grids. The results reveal a more realistic spatial pattern of
CO2 emission from transportation, which can be used to identify the
emission 'hot spots'. Of the four highest transportation-related
CO2 emission hotspots in Louisiana, high-emission grids literally covered
the entire East Baton Rouge Parish and Orleans Parish, whereas
CO2 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.
