Application of a Spatially Explicit Scaling Factor Method on CO2 Emissions From New York

<p>Assessing progress towards greenhouse gas mitigation targets in recent legislation requires reliable, precise methods for emissions quantification.&#160; Top-down approaches can provide a complementary assessment to the bottom-up inventories typically used by cities.</p><p>In this work we have performed a series of 9 winter aircraft measurement flights downwind of New York City in 2018 &#8211; 2020.&#160; We use dispersion modeling driven by publicly available meteorological products to calculate footprints relevant to the flight data.&#160; To calculate modeled emissions, we combine these footprints with four CO₂ inventories (ODIAC, EDGAR, ACES, and Vulcan) using a spatially explicit scaling factor approach.&#160; We show that we can isolate the emissions from two areas of interest, New York City and the New York-Newark urban area, by using the fraction of modeled enhancements originating in said areas of interest as weighting functions.&#160; We then calculate a scaling factor that optimizes agreement with measurements for each flight.&#160; Here we discuss this technique and the posterior emissions for both areas of interest as compared to inversion analyses for the same areas.&#160; We also quantify the variability across the ensemble including multiple meteorological products, scaling factor calculation methods, and mixing parameterizations across all inventories and flight days.</p>