Evaluating nighttime lights and population distribution as proxies for mapping anthropogenic CO2 emission in Vietnam, Cambodia and Laos
Abstract
Keeping track of spatiotemporal changes of the greenhouse gases (GHG) emissions is key to the successful implementation of the United Nations Framework Convention on Climate Change (UNFCCC) as monitoring emissions directly informs international climate change policy initiatives. And while emission inventories often provide a robust tool to track emission trends at the country level, subnational emission estimates are often not reported or reports vary in robustness as the estimates are often dependent on the spatial modeling approach and ancillary data used to disaggregate the emission inventories. Assessing the errors and uncertainties of the subnational emission estimates is fundamentally challenging due to the lack of physical measurements at the subnational level. To begin addressing the current performance of modeled gridded CO2 emissions, this study compares two common proxies used to disaggregate CO2 emission estimates. We use a known gridded CO2 model based on satellite-observed nighttime light (NTL) data (Open Source Data Inventory for Anthropogenic CO2, ODIAC) and a gridded population dataset driven by a set of ancillary geospatial data. We examine the association at multiple spatial scales of these two datasets for three countries in Southeast Asia: Vietnam, Cambodia and Laos and characterize the spatiotemporal similarities and differences for 2000, 2005, and 2010. We specifically highlight areas of potential uncertainty in the ODIAC model, which relies on the single use of NTL data for disaggregation of the non-point emissions estimates. Results show, over time, how a NTL-based emissions disaggregation tends to concentrate CO2 estimates in different ways than population-based estimates at the subnational level. We highlight with the findings differences in the NTL and population datasets to estimate subnational CO2 emissions for a region where development and shifts in population distribution are uneven from 2000-2010 with varying growth trajectories that are country and region specific.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFMGC53H1236G
- Keywords:
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- 1622 Earth system modeling;
- GLOBAL CHANGE;
- 1990 Uncertainty;
- INFORMATICS;
- 3275 Uncertainty quantification;
- MATHEMATICAL GEOPHYSICS