Cost uncertainties and ecological impacts drive tradeoffs between electrical system decarbonization pathways in New England, U.S.A.

Amir M. Gazar^1,2, Chloe Jackson³, Georgia Mavrommati³, Rich B. Howarth⁴, Ryan S.D. Calder^1,2,5,*

¹Dept. of Population Health Sciences, Virginia Tech, Blacksburg, VA, 24061, USA
²Global Change Center, Virginia Tech, Blacksburg, VA, 24061, USA
³School for the Environment, University of Massachusetts Boston, Boston, MA, 02125, USA
⁴Environmental Program, Dartmouth College, Hanover, NH, 03755, USA
⁵Department of Civil and Environmental Engineering, Duke University, Durham, NC, 27708, USA
* Contact: rsdc@vt.edu

Abstract

Advocates, researchers and policymakers seek characterizations of tradeoffs from diverse decarbonization pathways beyond outputs of optimization models, and robust quantification of uncertainties. We develop and apply to New England, U.S.A. an hourly-scale probabilistic model accepting portfolio decisions and demand as inputs and simulating costs and impacts through 2050. In New England pathway incorporating small modular reactors lowers total social costs but increases cost uncertainties compared to the target “all options” pathway currently guiding policymakers ($470 ± 97 billion vs. $477 ± 87.5 billion by 2050). New natural gas minimizes direct monetary costs, but monetized impacts vastly outweigh these savings compared to decarbonized pathways (e.g., $262 billion above “all options”). Likewise, land use varies from negligible to 9,890 km² across pathways. Tracking uncertainties correlated across pathways improves decision support (e.g., >90% confidence that constraining transmission with Canada increases costs by ≥ $19.4 billion despite overlapping 90% CIs for absolute costs).

Keywords: integrated assessment model; discount rate; capacity expansion model; decarbonization; renewable energy; energy policy; cost-benefit analysis

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Reproduction Information Document

A comprehensive step-by-step guide to reproduce every analysis in this repository:

• Section 1: Configuration & setup, hardware (macOS 14.5 Sonoma, ARC cluster), R 4.4.2 & RStudio 2024.09.1, package versions, install & run times.
• Section 2: Conceptual overview of the modeling framework and code availability.
• Section 3: Decarbonization pathways data processing (Excel → R, metadata tagging, year‐range extraction).
• Section 4: Generation expansion model scripts, hourly wind/solar CFs, SMR specs, fossil facility & emissions processing, new fossil additions, imports, demand processing, randomization, dispatch‐curve generation.
• Section 5: Dispatch‐curve results processing.
• Section 6: Total cost modules; CAPEX, FOM, VOM for fossil, non-fossil & imports; fuel & import cost adjustments; GHG & air pollutant emissions cost interpolation & NPV; unmet demand penalties; hydropower cost assumptions & capacity modeling; consolidation of all costs.
• Section 7: Ecological impact metrics; land use, water withdrawals, avian mortality, viewshed.

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Copyrights and Citation

Gazar, A. M., Jackson, C., Mavrommati, G., Howarth, R. B., & Calder, R. (2025). Cost uncertainties and ecological impacts drive tradeoffs between electrical system decarbonization pathways in New England, U.S.A., Engineering Archive. https://doi.org/10.31224/4684

© 2025 Amir M. Gazar et al. All rights reserved. This work is licensed under a Creative Commons Attribution 4.0 International License .