Lisa Rennels

All Publications

• The Social Costs of Hydrofluorocarbons and the Large Climate Benefits from their Expedited Phasedown. Nature climate change Tan, T., Rennels, L., Parthum, B. 2024; 14: 55-60

  Abstract

  Hydrofluorocarbons are a potent greenhouse gas, yet there remains a lack of quantitative estimates of their social cost. The present study addresses this gap by directly calculating the social cost of hydrofluorocarbons (SC-HFCs) using perturbations of exogenous inputs to integrated assessment models. We first develop a set of direct estimates of the SC-HFCs using methods currently adopted by the United States Government, and then derive updated estimates that incorporate recent advances in climate science and economics. We compare our estimates with commonly used social cost approximations based on global warming potentials to show that the latter is a poor proxy for direct calculation of hydrofluorocarbon emissions impacts using IAMs. Applying our SC-HFCs to the Kigali Amendment, a global agreement to phase down HFCs, we estimate that it provides $37 trillion (2020USD) in climate benefits over its lifetime. Expediting the phasedown could increase the estimated climate benefits to $41 trillion (2020USD).

  View details for DOI 10.1038/s41558-023-01898-9

  View details for PubMedID 38482130

  View details for PubMedCentralID PMC10936569

• Equity weighting increases the social cost of carbon Science Prest, B. C., Rennels, L. F., Errickson, F., Anthoff, D. 2024; 385 (6710): 715-717

  View details for DOI 10.1126/science.adn148

• How Domain Experts Use an Embedded DSL PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL Rennels, L., Chasins, S. E. 2023; 7 (OOPSLA)

  View details for DOI 10.1145/3622851

  View details for Web of Science ID 001087279100055

• Sea Level and Socioeconomic Uncertainty Drives High-End Coastal Adaptation Costs. Earth's future Wong, T. E., Ledna, C., Rennels, L., Sheets, H., Errickson, F. C., Diaz, D., Anthoff, D. 2022; 10 (12): e2022EF003061

  Abstract

  Sea-level rise and associated flood hazards pose severe risks to the millions of people globally living in coastal zones. Models representing coastal adaptation and impacts are important tools to inform the design of strategies to manage these risks. Representing the often deep uncertainties influencing these risks poses nontrivial challenges. A common uncertainty characterization approach is to use a few benchmark cases to represent the range and relative probabilities of the set of possible outcomes. This has been done in coastal adaptation studies, for example, by using low, moderate, and high percentiles of an input of interest, like sea-level changes. A key consideration is how this simplified characterization of uncertainty influences the distributions of estimated coastal impacts. Here, we show that using only a few benchmark percentiles to represent uncertainty in future sea-level change can lead to overconfident projections and underestimate high-end risks as compared to using full ensembles for sea-level change and socioeconomic parametric uncertainties. When uncertainty in future sea level is characterized by low, moderate, and high percentiles of global mean sea-level rise, estimates of high-end (95th percentile) damages are underestimated by between 18% (SSP1-2.6) and 46% (SSP5-8.5). Additionally, using the 5th and 95th percentiles of sea-level scenarios underestimates the 5%-95% width of the distribution of adaptation costs by a factor ranging from about two to four, depending on SSP-RCP pathway. The resulting underestimation of the uncertainty range in adaptation costs can bias adaptation and mitigation decision-making.

  View details for DOI 10.1029/2022EF003061

  View details for PubMedID 37035442

  View details for PubMedCentralID PMC10078412

• Comprehensive evidence implies a higher social cost of CO2. Nature Rennert, K., Errickson, F., Prest, B. C., Rennels, L., Newell, R. G., Pizer, W., Kingdon, C., Wingenroth, J., Cooke, R., Parthum, B., Smith, D., Cromar, K., Diaz, D., Moore, F. C., Müller, U. K., Plevin, R. J., Raftery, A. E., Ševčíková, H., Sheets, H., Stock, J. H., Tan, T., Watson, M., Wong, T. E., Anthoff, D. 2022; 610 (7933): 687-692

  Abstract

  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 Medicine1 (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. Here 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 $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with 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.

  View details for DOI 10.1038/s41586-022-05224-9

  View details for PubMedID 36049503

  View details for PubMedCentralID PMC9605864

• MimiBRICK.jl: A Julia package for the BRICK model for sea-level change in the Mimi integrated modeling framework Journal of Open Source Software Wong, T. E., Rennels, L. F., Errickson, F., Srikrishnan, V., Bakker, A., Keller, K., Anthoff, D. 2022; 7 (76)

  View details for DOI 10.21105/joss.04556

• The Social Cost of Carbon: Advances in Long-Term Probabilistic Projections of Population, GDP, Emissions, and Discount Rates BROOKINGS PAPERS ON ECONOMIC ACTIVITY Rennert, K., Prest, B. C., Pizer, W. A., Newell, R. G., Anthoff, D., Kingdon, C., Rennels, L., Cooke, R., Raftery, A. E., Sevcikova, H., Errickson, F. 2021: 223-305

  View details for DOI 10.1353/eca.2022.0003

  View details for Web of Science ID 000824167700004

• Projecting future costs to U.S. electric utility customers from power interruptions. Energy (Oxford, England) Larsen, P. H., Boehlert, B., Eto, J., Hamachi-LaCommare, K., Martinich, J., Rennels, L. 2018; 147: 1256-1277

  Abstract

  This analysis integrates regional models of power system reliability, output from atmosphere-ocean general circulation models, and results from the Interruption Cost Estimate (ICE) Calculator to project long-run costs to electric utility customers from power interruptions under different future severe weather and electricity system scenarios. We discuss the challenges when attempting to model long-run costs to utility customers including the use of imperfect metrics to measure severe weather. Despite these challenges, initial findings show that discounted cumulative customer costs, through the middle of the century, could range from $1.5-$3.4 trillion ($2015) without aggressive undergrounding of the power system and increased utility operations and maintenance (O&M) spending and $1.5-$2.5 trillion with aggressive undergrounding and increased spending. By the end of the century, cumulative customer costs could range from $1.9-$5.6 trillion (without aggressive undergrounding and increased spending) and $2.0-$3.6 trillion (with aggressive undergrounding and increased spending). We find that, in some scenarios, aggressive undergrounding of distribution lines and increased O&M spending is not always cost-effective. We conclude by identifying important topics for follow-on research, which have the potential to improve the cost estimates of this model.

  View details for DOI 10.1016/j.energy.2017.12.081

  View details for PubMedID 31728076

  View details for PubMedCentralID PMC6855308

• Climate Change Impacts on Harmful Algal Blooms in U.S. Freshwaters: A Screening-Level Assessment. Environmental science & technology Chapra, S. C., Boehlert, B., Fant, C., Bierman, V. J., Henderson, J., Mills, D., Mas, D. M., Rennels, L., Jantarasami, L., Martinich, J., Strzepek, K. M., Paerl, H. W. 2017; 51 (16): 8933-8943

  Abstract

  Cyanobacterial harmful algal blooms (CyanoHABs) have serious adverse effects on human and environmental health. Herein, we developed a modeling framework that predicts the effect of climate change on cyanobacteria concentrations in large reservoirs in the contiguous U.S. The framework, which uses climate change projections from five global circulation models, two greenhouse gas emission scenarios, and two cyanobacterial growth scenarios, is unique in coupling climate projections with a hydrologic/water quality network model of the contiguous United States. Thus, it generates both regional and nationwide projections useful as a screening-level assessment of climate impacts on CyanoHAB prevalence as well as potential lost recreation days and associated economic value. Our projections indicate that CyanoHAB concentrations are likely to increase primarily due to water temperature increases tempered by increased nutrient levels resulting from changing demographics and climatic impacts on hydrology that drive nutrient transport. The combination of these factors results in the mean number of days of CyanoHAB occurrence ranging from about 7 days per year per waterbody under current conditions, to 16-23 days in 2050 and 18-39 days in 2090. From a regional perspective, we find the largest increases in CyanoHAB occurrence in the Northeast U.S., while the greatest impacts to recreation, in terms of costs, are in the Southeast.

  View details for DOI 10.1021/acs.est.7b01498

  View details for PubMedID 28650153

• Estimating wildfire response costs in Alaska's changing climate CLIMATIC CHANGE Melvin, A. M., Murray, J., Boehlert, B., Martinich, J. A., Rennels, L., Rupp, T. 2017; 141 (4): 783-795

  View details for DOI 10.1007/s10584-017-1923-2

  View details for Web of Science ID 000396826200014

• Climate Change Impacts on US Water Quality Using Two Models: HAWQS and US Basins WATER Fant, C., Srinivasan, R., Boehlert, B., Rennels, L., Chapra, S. C., Strzepek, K. M., Corona, J., Allen, A., Martinich, J. 2017; 9 (2)

  View details for DOI 10.3390/w9020118

  View details for Web of Science ID 000395435800048

• Climate change damages to Alaska public infrastructure and the economics of proactive adaptation. Proceedings of the National Academy of Sciences of the United States of America Melvin, A. M., Larsen, P., Boehlert, B., Neumann, J. E., Chinowsky, P., Espinet, X., Martinich, J., Baumann, M. S., Rennels, L., Bothner, A., Nicolsky, D. J., Marchenko, S. S. 2017; 114 (2): E122-E131

  Abstract

  Climate change in the circumpolar region is causing dramatic environmental change that is increasing the vulnerability of infrastructure. We quantified the economic impacts of climate change on Alaska public infrastructure under relatively high and low climate forcing scenarios [representative concentration pathway 8.5 (RCP8.5) and RCP4.5] using an infrastructure model modified to account for unique climate impacts at northern latitudes, including near-surface permafrost thaw. Additionally, we evaluated how proactive adaptation influenced economic impacts on select infrastructure types and developed first-order estimates of potential land losses associated with coastal erosion and lengthening of the coastal ice-free season for 12 communities. Cumulative estimated expenses from climate-related damage to infrastructure without adaptation measures (hereafter damages) from 2015 to 2099 totaled $5.5 billion (2015 dollars, 3% discount) for RCP8.5 and $4.2 billion for RCP4.5, suggesting that reducing greenhouse gas emissions could lessen damages by $1.3 billion this century. The distribution of damages varied across the state, with the largest damages projected for the interior and southcentral Alaska. The largest source of damages was road flooding caused by increased precipitation followed by damages to buildings associated with near-surface permafrost thaw. Smaller damages were observed for airports, railroads, and pipelines. Proactive adaptation reduced total projected cumulative expenditures to $2.9 billion for RCP8.5 and $2.3 billion for RCP4.5. For road flooding, adaptation provided an annual savings of 80-100% across four study eras. For nearly all infrastructure types and time periods evaluated, damages and adaptation costs were larger for RCP8.5 than RCP4.5. Estimated coastal erosion losses were also larger for RCP8.5.

  View details for DOI 10.1073/pnas.1611056113

  View details for PubMedID 28028223

  View details for PubMedCentralID PMC5240706