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Implications of climate change mitigation strategies on international bioenergy trade
Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade. © 2020, The Author(s).
Bioenergy technologies in long-run climate change mitigation: results from the EMF-33 study
Bioenergy is expected to play an important role in long-run climate change mitigation strategies as highlighted by many integrated assessment model (IAM) scenarios. These scenarios, however, also show a very wide range of results, with uncertainty about bioenergy conversion technology deployment and biomass feedstock supply. To date, the underlying differences in model assumptions and parameters for the range of results have not been conveyed. Here we explore the models and results of the 33rd study of the Stanford Energy Modeling Forum to elucidate and explore bioenergy technology specifications and constraints that underlie projected bioenergy outcomes. We first develop and report consistent bioenergy technology characterizations and modeling details. We evaluate the bioenergy technology specifications through a series of analyses—comparison with the literature, model intercomparison, and an assessment of bioenergy technology projected deployments. We find that bioenergy technology coverage and characterization varies substantially across models, spanning different conversion routes, carbon capture and storage opportunities, and technology deployment constraints. Still, the range of technology specification assumptions is largely in line with bottom-up engineering estimates. We then find that variation in bioenergy deployment across models cannot be understood from technology costs alone. Important additional determinants include biomass feedstock costs, the availability and costs of alternative mitigation options in and across end-uses, the availability of carbon dioxide removal possibilities, the speed with which large scale changes in the makeup of energy conversion facilities and integration can take place, and the relative demand for different energy services. © 2020, The Author(s).
The value of climate-resilient seeds for smallholder adaptation in sub-Saharan Africa
Climate change is threatening food security in many tropical countries, where a large proportion of food is produced by vulnerable smallholder farmers. Interventions are available to offset many of the negative impacts of climate change on agriculture, and they can be tailored to local conditions often through relative modest investments. However, little quantitative information is available to guide investment or policy choices at a time when countries and development agencies are under pressure to implement policies that can help achieve Sustainable Development Goals while coping with climate change. Among smallholder adaptation options, developing seeds resilient to current and future climate shocks expected locally is one of the most important actions available now. In this paper, we used national and local data to estimate the costs of climate change to smallholder farmers in Malawi and Tanzania. We found that the benefits from adopting resilient seeds ranged between 984 million and 2.1 billion USD during 2020–2050. Our analysis demonstrates the benefits of establishing and maintaining a flexible national seed sector with participation by communities in the breeding, delivery, and adoption cycle. © 2020, The Author(s).
Responsibility Under Uncertainty: Which Climate Decisions Matter Most?
We propose a new method for estimating how much decisions under monadic uncertainty matter. The method is generic and suitable for measuring responsibility in finite horizon sequential decision processes. It fulfills “fairness” requirements and three natural conditions for responsibility measures: agency, avoidance and causal relevance. We apply the method to study how much decisions matter in a stylized greenhouse gas emissions process in which a decision maker repeatedly faces two options: start a “green” transition to a decarbonized society or further delay such a transition. We account for the fact that climate decisions are rarely implemented with certainty and that their consequences on the climate and on the global economy are uncertain. We discover that a “moral” approach towards decision making — doing the right thing even though the probability of success becomes increasingly small — is rational over a wide range of uncertainties.
Optimal carbon taxation and horizontal equity: A welfare-theoretic approach with application to German household data
We develop a model of optimal taxation and redistribution under an ambitious climate target. We take into account vertical income differences, but also explicitly capture horizontal equity concerns by considering heterogeneous energy efficiencies. By deriving first- and second-best rules for policy instruments including carbon and labor taxes, transfers and energy subsidies, we investigate analytically how vertical and horizontal inequality is considered in the welfare maximizing tax structure. We calibrate the model to German household data and a 30 percent emission reduction goal and show that redistribution of carbon tax revenues via household-specific transfers is the first-best policy. Under plausible assumptions on inequality aversion, transfers to energy-intensive households should be about five times higher than transfers to energy-efficient households. Equal per-capita transfers do not require to observe households’ efficiency type, but increase equity-weighted mitigation costs by around 5 percent compared to the first-best. Mitigation costs increase by less, if the government can implement a uniform clean energy subsidy or household-specific tax-subsidy schemes on energy consumption and labor income that target heterogeneous energy efficiencies. Horizontal equity concerns may therefore constitute a new second-best rationale for clean energy policies or differentiated energy taxes.
Reducing stranded assets through early action in the Indian power sector
Cost-effective achievement of the Paris Agreement's long-term goals requires the unanimous phase-out of coal power generation by mid-century. However, continued investments in coal power plants will make this transition difficult. India is one of the major countries with significant under construction and planned increase in coal power capacity. To ascertain the likelihood and consequences of the continued expansion of coal power for India's future mitigation options, we use harmonised scenario results from national and global models along with projections from various government reports. Both these approaches estimate that coal capacity is expected to increase until 2030, along with rapid developments in wind and solar power. However, coal capacity stranding of the order of 133–237 GW needs to occur after 2030 if India were to pursue an ambitious climate policy in line with a well-below 2 °C target. Earlier policy strengthening starting after 2020 can reduce stranded assets (14–159 GW) but brings with it political economy and renewable expansion challenges. We conclude that a policy limiting coal plants to those under construction combined with higher solar targets could be politically feasible, prevent significant stranded capacity, and allow higher mitigation ambition in the future.