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We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.
Elevated annual average temperature has been found to impact macro-economic growth. However, various fundamental elements of the economy are affected by deviations of daily temperature from seasonal expectations which are not well reflected in annual averages. Here we show that increases in seasonally adjusted day-to-day temperature variability reduce macro-economic growth independent of and in addition to changes in annual average temperature. Combining observed day-to-day temperature variability with subnational economic data for 1,537 regions worldwide over 40 years in fixed-effects panel models, we find that an extra degree of variability results in a five percentage-point reduction in regional growth rates on average. The impact of day-to-day variability is modulated by seasonal temperature difference and income, resulting in highest vulnerability in low-latitude, low-income regions (12 percentage-point reduction). These findings illuminate a new, global-impact channel in the climate–economy relationship that demands a more comprehensive assessment in both climate and integrated assessment models.
Global emissions scenarios play a critical role in the assessment of strategies to mitigate climate change. The current scenarios, however, are criticized because they feature strategies with pronounced overshoot of the global temperature goal, requiring a long-term repair phase to draw temperatures down again through net-negative emissions. Some impacts might not be reversible. Hence, we explore a new set of net-zero CO2 emissions scenarios with limited overshoot. We show that upfront investments are needed in the near term for limiting temperature overshoot but that these would bring long-term economic gains. Our study further identifies alternative configurations of net-zero CO2 emissions systems and the roles of different sectors and regions for balancing sources and sinks. Even without net-negative emissions, CO2 removal is important for accelerating near-term reductions and for providing an anthropogenic sink that can offset the residual emissions in sectors that are hard to abate.
Process-based integrated assessment models (IAMs) project long-term transformation pathways in energy and land-use systems under what-if assumptions. IAM evaluation is necessary to improve the models’ usefulness as scientific tools applicable in the complex and contested domain of climate change mitigation. We contribute the first comprehensive synthesis of process-based IAM evaluation research, drawing on a wide range of examples across six different evaluation methods including historical simulations, stylised facts, and model diagnostics. For each evaluation method, we identify progress and milestones to date, and draw out lessons learnt as well as challenges remaining. We find that each evaluation method has distinctive strengths, as well as constraints on its application. We use these insights to propose a systematic evaluation framework combining multiple methods to establish the appropriateness, interpretability, credibility, and relevance of process-based IAMs as useful scientific tools for informing climate policy. We also set out a programme of evaluation research to be mainstreamed both within and outside the IAM community.
The goal of limiting global warming to well below 2°C as set out in the Paris Agreement calls for a strategic assessment of societal pathways and policy strategies. Besides policy makers, new powerful actors from the private sector, including finance, have stepped up to engage in forward-looking assessments of a Paris-compliant and climate-resilient future. Climate change scenarios have addressed this demand by providing scientific insights on the possible pathways ahead to limit warming in line with the Paris climate goal. Despite the increased interest, the potential of climate change scenarios has not been fully unleashed, mostly due to a lack of an intermediary service that provides guidance and access to climate change scenarios. This perspective presents the concept of a climate change scenario service, its components, and a prototypical implementation to overcome this shortcoming aiming to make scenarios accessible to a broader audience of societal actors and decision makers.
Controlling bioenergy-induced land-use-change emissions is key to exploiting bioenergy for climate change mitigation. However, the effect of different land-use and energy sector policies on specific bioenergy emissions has not been studied so far. Using the global integrated assessment model REMIND-MAgPIE, we derive a biofuel emission factor (EF) for different policy frameworks. We find that a uniform price on emissions from both sectors keeps biofuel emissions at 12 kg CO2 GJ−1. However, without land-use regulation, the EF increases substantially (64 kg CO2 GJ−1 over 80 years, 92 kg CO2 GJ−1 over 30 years). We also find that comprehensive coverage (>90%) of carbon-rich land areas worldwide is key to containing land-use emissions. Pricing emissions indirectly on the level of bioenergy consumption reduces total emissions by cutting bioenergy demand but fails to reduce the average EF. In the absence of comprehensive and timely land-use regulation, bioenergy thus may contribute less to climate change mitigation than assumed previously.
Under current land-use regulation, carbon dioxide emissions from biofuel production exceed those from fossil diesel combustion. Therefore, international agreements need to ensure the effective and globally comprehensive protection of natural land before modern bioenergy can effectively contribute to achieving carbon neutrality.