Evaluation Of Gridded Co2 Emissions From Night-Time Lights Compared With Geospatially-Derived Population Distributions For Vietnam, Cambodia, And Laos

Tracking spatiotemporal changes in subnational greenhouse gas (GHG) emissions is key for the successful implementation of the United Nations Framework Convention on Climate Change (UNFCCC). To address the current performance of subnational CO2 emissions modeling and identify potential sources of errors and uncertainties, this study spatially compares two downscaled gridded CO2 datasets, modeled using nighttime lights satellite (NTL) data at a spatial resolution of 1km (ODIAC), to the corresponding temporally-explicit gridded population datasets parameterized using a set of geospatial covariates not including NTL data with the same resolution for the years 2000, 2005, and 2010. We do so for three countries in Southeast Asia: Vietnam, Laos and Cambodia, where emissions are likely to dramatically increase over time, and the NTL might not work well as a proxy for CO2 emissions like it does in developed countries. Results highlight the discrepancies in spatial patterns between estimated CO2 emissions based on NTL data versus population distributions. The spatial differences between these data products should loosely serve as a proxy for the errors and uncertainties associated with the NTL-based downscaling. This study informs future emission modeling in practical ways to better represent subnational emissions especially with the use of advanced geospatial modeling outputs.