Long-term economic benefits of stabilizing warming without overshoot – the ENGAGE model intercomparison

Abstract

Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change and their related societal transformations. The current generation of scenarios, however, are criticized because they rely heavily on net negative CO2 emissions (NNCE) that result from allowing temperature limits to be temporarily exceeded. In this study we present a new set of emissions scenarios that exclude NNCE. We show that such scenarios require a more rapid near-term transformation with significant long-term gains for the economy (even without considering the benefits of avoided climate impacts). Scenarios that avoid temperature overshoot and NNCE are thus not only economically more attractive over the long term, they also involve lower climate risks. Our study further identifies possible alternative configurations of net-zero CO2 emissions systems and the distinct roles of different sectors and regions in order to balance emissions sources and sinks.

Reproducing complex simulations of economic impacts of climate change with lower-cost emulators

“…In terms of the results for the fluvial flooding sector, inclusion of non-target regions' quarterly climate variables with MLP caused a drastic jump in the performance of the emulators. This is puzzling because in the simulation of the impacts of fluvial flooding, effects of international trading are not considered explicitly (Kinoshita et al, 2018). We suspect this is caused by the leakage because of the characteristics of the simulation data used in this study.…”

“…Here, "economic models" refers to the methodologies by which bio/physical impacts are monetized regardless of their ways of monetization. We used the simulated economic impacts caused by changes in agricultural productivity (Iizumi et al, 2017;Fujimori et al, 2018), undernourishment (Hasegawa et al, 2016a), heat-related excess mortality (Honda et al, 2014), cooling/heating demand (Hasegawa et al, 2016b;Park et al, 2018), occupational-health cost (Takakura et al, 2017), hydropower generation capacity (Zhou et al, 2018b), thermal power generation capacity (Zhou et al, 2018a, c), fluvial flooding (Kinoshita et al, 2018), and coastal inundation (Tamura et al, 2019) due to climate change. In each sector, bio/physical impacts were modelled by specific processbased impact models, and then the impacts were monetized either by multiplying values of statistical life (VSL) (OECD, 2012) by the damage functions which translate bio/physical impacts into economic damages (Kinoshita et al, 2018;Tamura et al, 2019) or by a computational general equilibrium (CGE) model (Fujimori et al, 2012(Fujimori et al, , 2017.…”

Land‐based measures to mitigate climate change: Potential and feasibility by country

“…We do not provide sectoral estimates for other carbon prices as there were fewer available data. The IAM approach (sometimes referred to as a “top‐down” approach) adapts land sector data from the most recent IAM intercomparison database, ENGAGE (Riahi et al, 2021 ), and estimates cost‐effective potential (possible up to $100/tCO 2 eq) in 2050 across six models and 131 scenarios for seven land‐based measures in five regions. IAMs estimate economic potentials using carbon prices; therefore, we do not provide technical potential estimates from IAMs.…”

“…The IAM approach estimates economic mitigation potential in 2050, up to $100/tCO 2 eq in our assessment to compare to the sectoral data. The intermodel median and min‐max range is reported for seven land sector measures from six IAM models and 131 scenario runs in the ENGAGE (Riahi et al, 2021 ) database. Each IAM measure is described in Section 2.1.2 .…”

“…Global mitigation potentials of substituting fossil fuels were estimated for BECCS, biochar, and manure management, shown in pink outline bars, illustrating the median and 90 th percentile values. IAM estimates (range and median, up to $100/tCO 2 eq) are provided for the seven measures where data are available in the ENGAGE database (Riahi et al, 2021). Potential co-benefits are indicated with icons, and the average global mitigation "density" (cumulative mitigation potential divided by total hectares in 2020-2050) is noted for measures with available data [Colour figure can be viewed at wileyonlinelibrary.com] emission levels, higher than the global average of 20-30% to meet the 1.5°C pathway (Roe et al, 2019).…”