Towards understanding the variability in source contribution of CO2 using high-resolution simulations of atmospheric δ13CO2 signatures in the Greater Toronto Area, Canada

Abstract

Stable carbon isotopic signatures (δ13C) can provide insight into sectors of anthropogenic activities emitting carbon dioxide (CO2) in situations where signatures of unique end-members are known. We present an atmospheric modelling framework that combines local δ13C signatures of combustion fuels with the Southern Ontario CO2 Emissions (SOCE) inventory to simulate ambient δ13CO2 signatures in the Greater Toronto Area. We demonstrate that the modelled δ13CO2 captures the variability in measured hourly signatures at the Downsview station from January to March, 2016 as well as the diurnal profile of signatures. We then use our ability to model δ13CO2 to assess traditional isotopic mass balance (IMB) and Keeling and Miller-Tans analysis. We performed three IMB to estimate the δ13CO2 signature of the local CO2 enhancement (δ13Cs) for measured and modelled data (using two background estimates: 5th percentile of a 48-hour running average and output from the Copernicus Atmospheric Monitoring Service (CAMS)). We found that when the 5th percentile was used as a background estimate, the δ13Cs was often unrealistic and isotopically heavier compared to that using CAMS. We compared IMB with Keeling analyses based on both overnight and hour-of-day data. For both approaches, when Keeling analyses were run on modelled and measured data, the median δ13C signature of the CO2 sources was more variable and on average heavier than the source attribution in the SOCE inventory. Because this issue occurred using both the measurements and the model simulation, it indicates potential issues with these approaches for independent observational constraints on source attribution.