Downscaling fossil-fuel CO2 emissions to policy relevant scales: Current errors and biases, expected improvements, and future perspectives
Authors: Oda Tomohiro , Bun Rostyslav , Román Miguel , Wang Zhuosen , Shrestha Ranjay , Lauvaux Thomas , Richao Cong , Saito Makoto , Nishihashi Masahide , Terao Yukio , Maksyutov Shamil , Matthews Bradley , Anderl Michael , Ott Lesley , Pawson Steven 
Published: March 2020

&lt;p&gt;Many of the global and regional gridded emission inventories used in atmospheric are based on downscaling techniques. &amp;#160;Regardless of their limitations compared to locally-constructed mechanistic emission inventories, such gridded datasets will keep a key role of transferring the information reported as emission inventories into science-based emission verification support (EVS) systems. &amp;#160;Given the use of inverse modeling in the EVS systems, characterizing errors and biases associated with the downscaled emission field is critical in order to obtain robust verification results.&amp;#160; However, such error characterization is often challenging due to the lack of objective metrics.&amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160; This study compares downscaled emissions from the ODIAC global high-resolution dataset to values taken from the reported inventories and from other independent emission products with the intent of assessing the validity (e.g., error, bias, or accuracy ) of downscaled emissions databases at different policy relevant scales. &amp;#160;ODIAC is based on its flagship high-resolution emission downscaling using satellite-observed nighttime lights (NTL) and point source information.&amp;#160; The sole use of the NTL proxy for diffuse emissions has limitations.&amp;#160; However, that provides a good opportunity to solely evaluate the performance of NTL as an emission proxy.&amp;#160; It is now relatively straightforward to create detailed, high-resolution emission maps due to the advancements in geospatial modeling.&amp;#160; However, such geospatial modeling techniques, which combine multiple pieces of information from different sources, are often neither validated nor even carefully evaluated.&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160; As commonly done in previous emission uncertainty studies, we use the differences and agreements as a proxy for errors and improvements. &amp;#160;We collect emission information reported at policy relevant scales, such as state/province/prefecture, cities and facility level (only for point sources).&amp;#160; We also use locally-constructed fine-grained emission inventories as a quasi-truth for the emission distribution.&amp;#160; We also assess the performance of NASA&amp;#8217;s Black Marble NTL product suites as a new emission proxy in relation to current the ODIAC proxy that is based on older NTL datasets.&amp;#160; We also look at how these emission differences translate into atmospheric concentration differences using high-resolution WRF simulations.&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&amp;#160;&amp;#160;&amp;#160; Based on results from the comparison, we identify and discuss the challenges and limitations in the use of downscaled emissions in carbon monitoring at different policy-relevant scales, especially at the city level, and propose possible ways to overcome some of the challenges and provide emission fields that are useful for both science and policy applications.&amp;#160;&amp;#160;&amp;#160;&lt;/p&gt;