232 research outputs found
The economic impact of substantial sea-level rise
No full textUsing the FUND model, an impact assessment is conducted over the 21st century for rises in sea level of up to 2-m/century and a range of socio-economic scenarios downscaled to the national level, including the four SRES (IPCC Special Report on Emissions Scenarios) storylines. Unlike a traditional impact assessment, this analysis considers impacts after balancing the costs of retreat with the costs of protection, including the effects of coastal squeeze. While the costs of sea-level rise increase with greater rise due to growing damage and protection costs, the model suggests that an optimum response in a benefit-cost sense remains widespread protection of developed coastal areas, as identified in earlier analyses. The socio-economic scenarios are also important in terms of influencing these costs. In terms of the four components of costs considered in FUND, protection dominates, with substantial costs from wetland loss under some scenarios. The regional distribution of costs shows that a few regions experience most of the costs, especially East Asia, North America, Europe and South Asia. Importantly, this analysis suggests that protection is much more likely and rational than is widely assumed, even with a large rise in sea level. This is underpinned by the strong economic growth in all the SRES scenarios: without this growth, the benefits of protection are significantly reduced. It should also be noted that some important limitations to the analysis are discussed, which collectively suggest that protection may not be as widespread as suggested in the FUND results
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Leveraging the Bioeconomy for Carbon Drawdown
No full textAbstractLeveraging the Bioeconomy for Carbon Drawdown
By
John Paul Dees
Doctor of Philosophy in Energy and Resources
University of California, Berkeley
Professors Daniel M. Kammen and David Anthoff, Co-chairsThe role of the bioeconomy in climate change mitigation has been, at times, both contested or framed in a limited manner to include only bioenergy with carbon capture and sequestration (BECCS) technologies. This dissertation contributes to a more expansive framework wherein the bioeconomy services distinct and dynamic near, medium, and long-term decarbonization needs. Products of the bioeconomy can serve as both fossil fuel replacement in “hard-to-abate” sectors as well as providing a carbon storage medium for biomass carbon removal and storage (BiCRS), an emerging framework with a more expansive opportunity set for carbon removal than BECCS alone. This dissertation builds on existing literature, starting with a review of the BiCRS literature and a supplementary novel analysis of the climate impact potential of BiCRS technologies in the near-term. The subsequent chapters offer cost and climate impact assessments for biomass utilization in the transportation sector. The bioeconomy already services substantial decarbonization needs in light duty transportation in the form of biofuels derived from starch, sugars, and oil crops. Chapter 3 explores the potential to further decarbonize ethanol production by capturing fossil boiler emissions via the integration of an oxyfuel boiler. Chapter 4 explores the potential of drop-in biofuels in the “hard to abate” aviation sector through a comparative analysis of the cost, climate impact, and scalability of sustainable aviation fuel technologies and feedstocks. The overarching finding of this dissertation is that there are meaningful, cost-effective opportunities to deploy bio-based products for decarbonization and carbon removal, particularly in economic sectors where there are few if any other near-term options.Stringent climate change mitigation scenarios rely on large-scale drawdown of carbon dioxide from the atmosphere. Amongst drawdown technologies, BECCS has received considerable attention in the climate mitigation literature. Recently, attention has shifted further from a relatively narrow focus on BECCS to a broader focus on BiCRS. The concept of BiCRS has the potential to enable a future where the climate mitigation value of biomass resources is more valuable than the energy value, due to the potential to remove and sequester large quantities of atmospheric CO2. There are numerous opportunities to incorporate carbon removal and management within the bioeconomy, but the majority of immediate carbon removal potential exists in four bioproducts: bioenergy, bioplastics, biochar, and wood products. Chapter 2 analyzes the life cycle greenhouse gas emissions and disposition of sequestered carbon over 10,000 years for four bioproducts representative of each broader category: an advanced BECCS pathway, biopolyethylene, oriented strand board, and biochar soil amendment. The analysis shows that the BECCS pathway has the greatest magnitude and durability of CO2 storage over all time horizons. However, non-BECCS pathways achieve 34-64% of the drawdown magnitude relative to BECCS and retain 55-67% of their initial drawdown over 100 years (central estimate). This work identifies three engineering strategies for enhancing carbon drawdown: reducing biomass supply chain emissions, maximizing carbon stored in long-lived products, and extending the term of carbon storage. In the larger context of this work, the analysis demonstrates that the bioeconomy can service potentially higher-value economic needs than the energy sector alone, while removing and storing atmospheric carbon over climate-relevant timeframes. Within the energy sector, the bioeconomy still has a near-term role to play in transport decarbonization. Decarbonization of transportation fuels represents one of the most vexing challenges for climate change mitigation. Biofuels derived from corn starch have offered modest life cycle greenhouse gas (GHG) emissions reductions over fossil fuels. This work shows that capture and storage of CO2 emissions from corn ethanol fermentation achieves ~58% reduction in the GHG intensity (CI) of ethanol at a levelized cost of 52 2.24, a /tCO2e. Sensitivity analysis reveals that carbon neutral or even carbon negative ethanol can be achieved when oxyfuel carbon capture is stacked with low-CI alternatives to grid power and fossil natural gas. Conservatively, fermentation and oxyfuel CCS can reduce the CI of conventional ethanol by a net 44-50 gCO2/MJ. Full implementation of interventions explored in the sensitivity analysis would reduce CI by net 79-85 gCO2/MJ. Integrated oxyfuel and fermentation CCS is shown to be cost effective under existing U.S. policy, offering near-term abatement opportunities.The role of biofuels is likely to diminish in ground transport as electrification provides more cost and climate effective alternatives. However, commercial aviation is not amenable to electrification at scale in the near future, thus there is an imminent role for the bioeconomy. Aviation is termed a “hard to abate” sector as there are few viable decarbonization options for air transport at present due to safety considerations, infrastructure, and technical hurdles. Drop-in sustainable aviation fuels (SAF) produced from biomass or CO2 are widely-viewed as the most viable near-term alternatives to fossil jet fuel. There are many technical pathways to produce SAF, and their costs and impact on climate and food systems differ significantly. The work presented here sets sustainability and cost criteria to produce 10 billion gallons of SAF in the United States by 2030 and assesses the viability of SAF production technologies and feedstocks against those criteria. The analysis indicates the greatest opportunity in the production of Fischer-Tropsch and Alcohol-to-Jet fuels. These production pathways are amenable to waste and residue feedstocks, minimizing the impact on food systems and land use emissions. Moreover, they are compatible with relatively low-cost carbon capture and sequestration technologies which can yield carbon negative fuels. Given existing U.S. policies, the technoeconomic assessment of these pathways indicates that in many contexts, subsidized costs may be competitive with commercial Jet-A.The scope of the work in this dissertation highlights the significant and varied roles that the bioeconomy can play in climate mitigation while recognizing that sustainable biomass is a limited resource that should be targeted at its highest value uses
Modeling uncertainty in integrated assessment of climate change: a multimodel comparison
No full textThe economics of climate change involves a vast array of uncertainties, complicating our understanding of climate change. This study explores uncertainty in baseline trajectories using multiple integrated assessment models commonly used in climate policy development. The study examines model and parametric uncertainties for population, total factor productivity, and climate sensitivity
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Policies for an Ecological Civilization
No full textChina’s ecological civilization concept claims a new, Chinese model of promoting economic growth while reducing environmental pollution at the same time. This dissertation uses interdisciplinary methods to analyze two of China’s flagship ecological civilization policies, the national carbon market and the Belt and Road Initiative. While the national carbon market exemplifies China’s changing approach to domestic environmental policy, the Belt and Road Initiative is carrying the Chinese model of ecological civilization overseas. The first part of this dissertation focuses on China’s national carbon market. I use a computable general equilibrium (CGE) model to assess the interactions between a national carbon market and China’s ongoing structural economic transition, thereby yielding macro-scale evidence and policy suggestions for how China can fulfill ecological civilization goals of increasing GDP while reducing carbon dioxide emissions. Next, I investigate the carbon market from a qualitative perspective, assessing how emissions accounting is used as a foundation for policy-making. I also explore the capacity building community that sustains the carbon market, asking broader questions about how Chinese neoliberalism informs the formation of the national carbon market. The second part of this dissertation focuses on the Belt and Road Initiative (BRI), situating it in the context of leakage, or relocation of production in response to environmental regulation. Through a novel empirical study, I test the assumption that BRI projects may be better or worse for the environment than other sources of finance. I then explore potential mechanisms of Chinese overseas finance exceptionalism, informing ongoing policy and advocacy debates about how to engage with the growing scale of China’s overseas investment
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Uncertainty, Inequality, and Global Climate Policy
No full textDespite decades of research on the science and potential impacts of climate change, considerable disagreement remains over how to balance the upfront costs of reducing greenhouse gas emissions with the benefits of avoiding future negative impacts. This disagreement persists, in part, because deep uncertainties in the climate system limit our understanding of how temperature and sea level will evolve over the coming centuries. The global nature and long timescales of climate change provide an additional challenge, as climate policy analysis requires difficult ethical judgments on how to value the well-being of individuals at different income levels and across generations. In this dissertation, I address these issues by using integrated assessment models (IAMs) to analyze how distributional equity concerns and previously neglected climate uncertainties affect climate policy design. In the first part, I calculate the optimal carbon dioxide mitigation policy when society accounts for the trade-off between mitigation costs, climate damages, and the climate and localized health consequences of changes in air pollutant co-emissions. The presence of health “co-benefits” leads to increased mitigation levels that may be consistent with a 2 °C target, but the magnitude of this effect crucially depends on independent air quality policies and the value society assigns to improvements in human health. In the second part, I use a Bayesian calibration framework and an ensemble of IAMs to quantify how parametric climate uncertainties affect the social cost of methane (SC-CH4). Despite accounting for the recent 25% upward revision to methane radiative forcing, the constrained models produce a mean SC-CH4 estimate 23% lower than the value recently used by the U.S. federal government. I also provide the first probabilistic equity-weighted SC-CH4 estimates and find that the U.S. value is more than an order of magnitude higher than sub-Saharan Africa’s. The third part of my dissertation focuses on low-probability, high-impact upper tail estimates of the social cost of carbon (SCC). In this analysis, I first show that the simple climate models from the IAMs used to calculate official U.S. SCC estimates do not pass relatively simple out-of-sample hindcast tests and exhibit impulse response behaviors that are inconsistent with current scientific understanding. I then couple the non-climate components of each IAM to a reduced complexity Earth system model and quantify how different treatments of parametric uncertainties affect 95th percentile SCC estimates. While failing to account for interactions between the uncertain parameters increases the 95th percentile SCC by more than 20%, following the official U.S. SCC climate uncertainty framework nearly doubles it
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The Economics of Climate Change Under Uncertainty and Engineering the Software for its Research
No full textEvaluation of the potential economic impacts of climate change are crucial for informed policy responses. Several decades of rigorous research devoted to this topic have advanced the field enormously, and still there remain areas of active debate and research seeking to address open questions and shortcomings of existing work. I seek to address critical limitations and lines of inquiry through three primary projects. Through these three projects I tackle aspects of two challenges. First, a lack of usable domain-specific computational tools can slow climate research, discourage collaboration, and pose barriers to transparency. Second, policymakers must design climate policy in the face of substantial, sometimes unresolvable uncertainty along several dimensions. A fourth, concurrent effort, the development of the Mimi computational platform for integrated assessment modeling, is a vital contribution to the computational infrastructure that enables my own research as well as that of the broader research and policymaking communities.Computational modeling and analysis are at the core of the research posed in both Chapters 2 and 3, and calls for new open-source, easy-to-use computational tools to promote research, transparency, and collaboration echo those across modern scientific and interdisciplinary domains. As a core developer of the Mimi platform , I produce high-quality open-source software aimed at supporting collaboration and making it possible for researchers, including myself, to investigate new research questions and more effectively support policy makers. A multitude of academic groups across several universities use the platform, and it also directly supports federal and state-level regulatory analysis. Mimi is the subject of the project described Chapter 1.In Chapter 1 we employ both observation and semi-structured interviews to learn about designing software in climate change economics domain and gather generalizable insights about the design of embedded domain specific languages. Programming tools are increasingly integral to research and analysis in myriad domains, including specialized areas with no formal relation to computer science. Embedded domain-specific languages (eDSLs) have the potential to serve these programmers while placing relatively light implementation burdens on language designers. However, barriers to eDSL use reduce their practical value and adoption. In this project, we aim to deepen our understanding of how programmers use eDSLs and identify user needs to inform future eDSL designs. We performed a contextual inquiry (9 participants) with domain experts using Mimi, an eDSL for climate change economics modeling. A thematic analysis identified five key themes, including: the interaction between the eDSL and the host language has significant and sometimes unexpected impacts on eDSL user experience, and users preferentially engage with domain-specific communities and code templates rather than host language resources. The needs uncovered in our study offer design considerations for future eDSLs and suggest directions for future DSL usability research.The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography, and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency, and uncertainty characterization of SC-CO2 estimates. In Chapter 2 we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is 44-413/t-CO2: 5-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2 percent, a value 3.6-times higher than the US government’s current value of $51/t-CO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source GIVE model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared to estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.Evaluating the economic impacts of climate change is crucial to inform climate policy. One typical approach to assessing mitigation policy options uses integrated climate-economy models to analyze tradeoffs between the costs of reducing greenhouse gas emissions and the benefits of avoiding climate damages. However, the economic impacts of climate change are both expansive and deeply uncertain--adding a hurdle to designing tractable climate policy. Analysis using integrated climate-economy models thus often fails to fully represent the downside risk--what if the chosen model(s) are wrong? The deep uncertainty characterizing these models poses challenges for policymakers. In Chapter 3 we address this challenge using a robust decision-making framework to evaluate mitigation policy. We show that a shift from a decision framework that maximizes expected outcomes to one that is averse to regret supports precaution in the face of uncertainty and faster emissions cuts than currently implemented. Uncertainties about socioeconomic trajectories and the magnitude and functional form of climate damages create asymmetric consequences from delayed or weak mitigation policy
JuliaData/Tables.jl: v1.12.0
No full textTables v1.12.0 Diff since v1.11.1 Merged pull requests: fix error in error (#350) (@ericphanson) Add UnROOT to INTEGRATIONS.md replacing UpROOT (#351) (@Moelf) remove LinearAlgebra as dependency (#356) (@longemen3000)Jacob Quinn, Bogumił Kamiński, David Anthoff, Milan Bouchet-Valat, Tamas K. Papp, Takafumi Arakaki, Rafael Schouten, Nick Robinson, mathieu17g, Okon Samuel, Jarrett Revels, ExpandingMan, Eric Hanson, Anthony Blaom, PhD, Alex Arslan, Jerry Ling, Jiahao Chen, Josh Day, José Bayoán Santiago Calderón, … Jacob Adenbaum. (2024). JuliaData/Tables.jl: v1.12.0 (v1.12.0). Zenodo. https://doi.org/10.5281/zenodo.1275313
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Internalising Externalities: Macro Methods for Tracking and Optimizing Social Welfare and Sustainability
No full textI investigate the systemic problem of economic externalities from multiple angles with the goal of improving the way that we formulate, quantify, evaluate, and advance economic welfare and environmental sustainability.Externalities are costs (or benefits) that result from economic activities and transactions which are not paid (received)1 by those directly involved. Some aspect of the cost or harm is external to the direct parties, which means that the market price is lower than it would otherwise be, with some part being ‘paid’ by others, usually in the form of some harm suffered. An example is air or water pollution caused by a factory: the firm has direct costs (materials, equipment, infrastructure, labour etc) which it, and potentially its customers, pay, but downwind and downstream communities suffer negative health and quality of life impacts that are not part of the costs paid by the producer or the consumer.Externalities undermine the theoretical optimum and welfare maximizing function of competitive markets, fundamentally skewing outcomes and causing major harm as a result of economic activity. Without accounting for externalities, the profit maximising and cost minimising impetus of markets guarantees harm, because it is always cheaper to undertake activities wherein some of the costs are not paid by the firm, while the revenues are realised directly. Issues of sustainability can be understood as negative externalities that impact the welfare of people in the future (Brundtland 1987).In my investigations, I generate novel analyses and tools for explaining, quantifying, and evaluating externalities. I complete assessments and analyses of the Genuine Progress Indicator (GPI) for California and the United States, and suggest improvements to its methodologies. The GPI is a macroeconomic indicator that incorporates assessments of a number of significant externalities in order to construct a more comprehensive measure of welfare. I produce a cross-sectional analysis of the Ecological Footprint (EF) efficiency in national welfare provision. EF measures the anthropogenic draw on renewable biological resources, the externality of unsustainable impact on natural resources. Finally, as a foundation for ongoing work examining externalities and related policy questions, I build an open source and free software package, MPSGE.jl, that facilitates easier Computer General Equilibrium (CGE) modelling. The equilibrium framework of CGE models lends itself to applications accounting for externalities, such as the imposition of Pigouvian taxes2.1 While there are both negative and positive externalities, in general I will default to the negative case for discussion throughout for readability, unless explicitly described otherwise.
2 Pigouvian taxes and subsidies (Pigou 1920) imposed and provided by the government, can adjust market prices to incorporate the externality cost, to more fully reflect and optimise social welfare.My GPI work, presented in Chapters 1 and 2, includes calculating and analysing the GPI of California and the United States in order to measure truer social welfare over time, while I also analyse the indicator and its strengths and weaknesses.In Chapter 1, we estimate the GPI for California for a five-year period, 2010-2014. Within this relatively short time period, which includes the recovery from the Great Recession, we examine how inequality, nonmarket activities, and environmental degradation, affects the GPI of California. We also evaluate our estimation of the California GPI (CA-GPI) in two specific ways. First, we compare California’s GPI to an alternative indicator of social welfare, the Human Development Index (HDI) for California. Our comparison points to the GPI as a more holistic measure of sustainable economic well-being, although the HDI is useful in evaluating educational attainment, life expectancy, or earnings across regions or demographic groups in the state. Second, we compare our estimation of CA-GPI to the California results from a GPI estimation for all fifty states for 2011, and evaluate how different methodological decisions and data selection affect the results. Comparison of the two GPI assessments shows how the use of region-specific data compared to scaled national data increases the accuracy of estimates. However, using data and methods that prioritizes standardization is essential for comparing the GPI across regions, though the trade-off is diminished regional accuracy. The chapter concludes with a discussion of the uses of the GPI to evaluate policies, and suggests fruitful steps forward.
Chapter 2 argues that important improvements in the Genuine Progress Indicator can be made by directly calculating the loss of natural resources, the benefits of leisure, and adjusting for inequality using a global norm, rather than using local, historical benchmarks. Local benchmarking is an obstacle to the standardisation and comparability of the GPI. We provide alternative methods for the five components that have used benchmarking in the standard GPI. We present new empirical estimates for the GPI of the United States and California over the period 1995 through 2017, calculated with and without the alternative methods. Using the alternative methods, we show that some differences between the GPI of the U.S. and CA are artefacts of the benchmark methods. Implementing the alternative methods narrows the gap between the U.S. and CA GPI, as it reduces the U.S. environmental costs, and removes the artificial differential between the U.S. and CA in the cost of inequality. We find that the GPI provides insight into net welfare not reflected in GDP, both with and without the benchmarking methods. Overall, we suggest that the GPI can be significantly improved with these high priority revisions without changing the fundamental approach or theoretical framework.In Chapter 3, I present a novel data analysis and visualization that combines indicators of different of national welfare in conjunction with each country’s associated Ecological Footprint, generating a measure of Ecological Footprint Efficiency, that is, the efficiency in providing economic services while minimizing the externality of ecological impact. The Ecological Footprint (EF) measures humanity’s draw on renewable biological resources. I use a specific set of data from a model which tracks the EF through the global supply chain to seven categories of final consumption. Using that EF data enables a direct association with selected data from the Sustainable Development Goals Indicator (SDGI) tracking the quality of the welfare benefits, under each of the seven categories.In Chapter 4, I detail my research contribution in developing MPSGE.jl, a novel, open-source software platform to facilitate simpler, error-reducing, fast, and free Computable General Equilibrium (CGE) modelling. The package is an evolution of the Mathematical Programming System for General Equilibrium analysis (MPSGE, Rutherford 1987) in the open-source Julia programming language. MPSGE.jl provides free and open-source access to the succinct-form model-construction functionality of its predecessor, and provides additional features such as an algebraic print of the model equations and easy integration with the growing ecosystem of other packages in the Julia programming language. I describe the package’s structure and use, and illustrate its benefits as part of a general-use and increasingly popular scientific programming language with an application. I use Monte Carlo methods to perform sensitivity analyses on a variety of parameters within a national model of the United States, and generate visualisations of the results with a standard plotting package
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