An inter-comparison of the social costs of air quality from reduced-complexity models

Elisabeth A. Gilmore, Jinhyok Heo, Nicholas Z. Muller, Christopher M Tessum, Jason D. Hill, Julian Marshall, Peter J. Adams

Research output: Contribution to journalArticlepeer-review

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Reliable estimates of externality costs - such as the costs arising from premature mortality due to exposure to fine particulate matter (PM2.5) - are critical for policy analysis. To facilitate broader analysis, several datasets of the social costs of air quality have been produced by a set of reduced-complexity models (RCMs). It is much easier to use the tabulated marginal costs derived from RCMs than it is to run 'state-of-the-science' chemical transport models (CTMs). However, the differences between these datasets have not been systematically examined, leaving analysts with no guidance on how and when these differences matter. Here, we compare per-tonne marginal costs from ground level and elevated emission sources for each county in the United States for sulfur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3) and inert primary PM2.5 from three RCMs: Air Pollution Emission Experiments and Policy (AP2), Estimating Air pollution Social Impacts Using Regression (EASIUR) and the Intervention Model for Air Pollution (InMAP). National emission-weighted average damages vary among models by approximately 21%, 31%, 28% and 12% for inert primary PM2.5, SO2, NOx and NH3 emissions, respectively, for ground-level sources. For elevated sources, emission-weighted damages vary by approximately 42%, 26%, 42% and 20% for inert primary PM2.5, SO2, NOx and NH3 emissions, respectively. Despite fundamental structural differences, the three models predict marginal costs that are within the same order of magnitude. That different and independent methods have converged on similar results bolsters confidence in the RCMs. Policy analyzes of national-level air quality policies that sum over pollutants and geographical locations are often robust to these differences, although the differences may matter for more source- or location-specific analyzes. Overall, the loss of fidelity caused by using RCMs and their social cost datasets in place of CTMs is modest.

Original languageEnglish (US)
Article number074016
JournalEnvironmental Research Letters
Issue number7
StatePublished - Jul 9 2019
Externally publishedYes

Bibliographical note

Funding Information:
This publication was developed by funding from the Center for Air, Climate and Energy Solutions under Assistance Agreement no. RD83587301 awarded by the US EPA. It has not been formally reviewed by the US EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. The US EPA does not endorse any products or commercial services mentioned in this publication. JH acknowledges the US Department of Energy (grant no. EE0004397) and the US Department of Agriculture (grant nos 2011-68005-30411 and MIN-12-083).

Publisher Copyright:
© 2019 The Author(s). Published by IOP Publishing Ltd.


  • Model inter-comparison
  • air quality
  • externality costs
  • particulate matter
  • policy analysis


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