Conference Agenda

Solar Geoengineering (SRM) temporarily offsets global warming but introduces a critical concern: the termination shock risk triggered by the sudden failure of SRM deployment. This study investigates the value of proactive adjustments of carbon abatement and SRM deployment in managing termination risk. We introduce termination shock as a stochastic regime-switching process into integrated assessment models that combine geophysical and economic dynamics. Then we propose a transformation technique that reformulates the stochastic model into a deterministic structure amenable to optimal control theory, overcoming the numerical challenges of dimensionality and non-stationarity. We find that, before the shock, a “myopic” decision-maker (DM) who ignores the shock, relies heavily on SRM and allows carbon emissions to rise steadily from 40 GtCO2/yr in 2020 to 78 GtCO2/yr by 2100. However, a forward-looking “smart” DM deploys only about half as much SRM and strengthens abatement to reverse the upward trend in emissions. After the shock, both DMs abandon SRM and sharply cut emissions below the “abatement-only” pathway. Although “smart” strategy incurs higher abatement costs and higher warming levels before the shock, it substantially reduces the post-shock temperature surge and secures GDP recovery to the “abatement-only” level—an unattainable recovery for “myopic” strategy. By 2100, it further narrows the GDP uncertainty range from 665–807 trillion USD (“myopic”) to 754–799 trillion USD. Sensitivity analyses show that the structure of “smart” strategy is robust across probabilities and damage specifications. Our findings contribute to management decisions in a potential future where SRM complements existing efforts to mitigate climate risks.

Solar geoengineering, also known as Solar Radiation Modification (SRM), provides rapid cooling that can reduce temperature-driven climate tipping point (CTP) risks, but it may simultaneously trigger carbon-driven CTPs by weakening incentives for emissions abatement. We extend the Dynamic Integrated Climate-Economy Model (DICE-2023) into a stochastic framework to examine the optimal mix of abatement and SRM under the collapse risk of coral reef ecosystems, an urgent CTP jointly driven by warming and acidification. The results show that: (1) without SRM, immediate and deep abatement is required to have a chance for preventing the ecosystems’ collapse, while abatement alone may still fail when ecosystems are highly sensitive to acidification; (2) combining abatement with SRM prevents the collapse while lowering considerable abatement burdens. These findings underscore the need to distinguish different drivers of CTPs in climate decision-making: abatement is required to address their root causes, while SRM is crucial for mitigating urgent risks.

Savanna ecosystems cover an ever-increasing proportion of the Earth’s surface and house a rapidly growing proportion of the world’s population and livestock. An often overlooked but urgent threat to savannas is posed by the process of woody encroachment, by which woodland encroaches upon grasslands used for livestock production, the principal means of subsistence in these areas. In this paper, we look at the impact of time-constant livestock and fire management on the resilience of savannas against bush encroachment in a well-known dynamic savanna model with tipping points. We contribute to the existing literature by studying the sensitivity of savanna resilience to economic, rather than purely physical, parameters. We find that higher livestock prices incentivize management that lowers the resilience of the system, eventually leading to its collapse. We also find that, under general conditions on the livestock dynamics, the proximity to the tipping point cannot be gleaned from vegetation quality, as it stays constant over livestock prices, while the savanna resilience decreases. Fire use makes the resilience of the savanna against woody encroachment more sensitive to changes in livestock prices if fixed livestock offtake and grazing intensity are chosen optimally.

Zimbabwe plays a crucial role in Africa’s drive to achieve zero carbon transition through its multiple initiatives to promote the utilization of its renewable energy (RE) potentials. However, not much is known about the drivers of RE consumption in this country. This study therefore sets out to interrogate the macroeconomic and environmental drivers of RE consumption in Zimbabwe. It used annual data spanning from 1990–2020. Employing the Autoregressive Distributed Lag (ARDL) bounds testing approach and the Error Correction Model (ECM), it assessed the long- and short-run dynamics between renewable energy use, human development index (HDI), population growth, trade openness, and rainfall variability. Results captured a long-run equilibrium relationship among the series. In the long run, HDI and rainfall variability positively influenced renewable energy consumption, while trade openness exerts a negative but significant effect, suggesting that improved human development fosters renewable energy adoption, whereas trade remains emission-intensive. In the short run, HDI and population growth display dynamic effects, reflecting socio-economic and demographic pressures. Granger causality tests indicate a unidirectional causality from renewable energy to HDI and a bidirectional link between HDI and trade openness, implying that renewable energy enhances welfare, while trade and human development reinforce each other. Econometric diagnostic and stability tests confirm the model’s robustness. Based on its findings, the study concludes that renewable energy development in Zimbabwe is shaped by socio-economic and climatic factors. It recommends policies that will promote renewable energy investment, human capital development, green trade expansion, and climate-responsive planning to ensure sustainable energy security and long-term economic growth.