Offsetting unabated agricultural emissions with CO2 removal to achieve ambitious climate targets

21st century. When analysing the individual contributions of GWP100-based offsetting, it shows that deviations are almost exclusively due to methane offsetting with negligible contri- butions from nitrous oxide (cf. S3 and S4 Figs). The use of alternative metrics, such as the GWP20 and the GWP�, only partially resolves these issues (cf. S4 Fig). Both metrics lead to ERF and temperature anomalies below the SSP1-2.6 baseline, thus overestimating the offset- ting requirements of additional methane, although these are significantly smaller using GWP�. While performing well in the first 20–40 years after the introduction of the policy but lead, by the end of the century GWP20-based offsetting results in up to 0.2˚C lower temperatures than in the SSP1-2.6 scenario. GWP� shows the opposite trend, with larger deviations immediately after the introduction of the policy (up to 0.05˚C), and almost no deviation by the end of the century. To conclude, GWP� performs significantly better than the traditional GWPs, yet it leads to slightly more offsetting than necessary. We therefore use the ERF-based offsetting rates in the remainder of this study. Our second set of results concerns the internalization of additional CDR costs via a tax on agricultural methane and nitrous oxide emissions, corresponding to the increase in mitigation cost under the alternative scenarios. Here, we use the costs to offset agricultural emissions via Fig 3. Radiative forcing and temperature anomaly under GWP100 offsetting compared to reference scenarios. Effective radiative forcing (ERF) and temperature

anomaly relative to the 1850–1900 average under the SSP1-2.6 scenario (SSP1-2.6), under the alternative emission scenario (constant or worst-case scenario), and under the offsetting scheme using the GWP100 metric. ERF and temperature anomalies result from all forcing agents taken into account by the FaIR model, including natural forcing from solar variability that causes the decadal scale cycle in ERF and temperature anomaly [64, 65]. Thick lines represent simulations with best-estimate parameters [65] whereas shaded areas encompass the 95%-interval of the ensemble simulations. a) ERF under the constant agricultural emission scenario. b) Change in temperature under the constant agricultural emission scenario. c) ERF under the worst-case agricultural emission scenario. d) Change in temperature under the worst-case agricultural emission scenario. https://doi.org/10.1371/journal.pone.0247887.g003 PLOS ONE Offsetting future agricultural emissions with CO2 removal PLOS ONE | https://doi.org/10.1371/journal.pone.0247887 March 17, 2021 9 / 19