Detection of fossil fuel emission trends in the presence of natural carbon cycle variability

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Abstract

Atmospheric CO2 observations have the potential to monitor regional fossil fuel emission (FFCO2) changes to support carbon mitigation efforts such as the Paris Accord, but they must contend with the confounding impacts of the natural carbon cycle. Here, we quantify trend detection time and magnitude in gridded total CO2 fluxes - the sum of FFCO2 and natural carbon fluxes - under an idealized assumption that monthly total CO2 fluxes can be perfectly resolved at a 2 2 resolution. Using Coupled Model Intercomparison Project 5 (CMIP5) 'business-as-usual' emission scenarios to represent FFCO2 and simulated net biome exchange (NBE) to represent natural carbon fluxes, we find that trend detection time for the total CO2 fluxes at such a resolution has a median of 10 years across the globe, with significant spatial variability depending on FFCO2 magnitude and NBE variability. Differences between trends in the total CO2 fluxes and the underlying FFCO2 component highlight the role of natural carbon cycle variability in modulating regional detection of FFCO2 emission trends using CO2 observations alone, particularly in the tropics and subtropics where mega-cities with large populations are developing rapidly. Using CO2 estimates alone at such a spatiotemporal resolution can only quantify fossil fuel trends in a few places - mostly limited to arid regions. For instance, in the Middle East, FFCO2 can explain more than 75% of the total CO2 trends in ∼70% of the grids, but only ∼20% of grids in China can meet such criteria. Only a third of the 25 megacities we analyze here show total CO2 trends that are primarily explained (>75%) by FFCO2. Our analysis provides a theoretical baseline at a global scale for the design of regional FFCO2 monitoring networks and underscores the importance of estimating biospheric interannual variability to improve the accuracy of FFCO2 trend monitoring. We envision that this can be achieved with a fully integrated carbon cycle assimilation system with explicit constraints on FFCO2 and NBE, respectively.

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Yin, Y., Bowman, K., Bloom, A. A., & Worden, J. (2019). Detection of fossil fuel emission trends in the presence of natural carbon cycle variability. Environmental Research Letters, 14(8). https://doi.org/10.1088/1748-9326/ab2dd7

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