Comparing Secondary Organic Aerosols Schemes Implemented in Current Chemical Transport Models and the Policy Implications of Uncertainties

Abstract. Secondary organic aerosol (SOA) constitutes a major component of fine particulate matter (PM2.5) that models must account for to assess how human activities influence air quality, climate, and public health. We characterize the current state of SOA modeling by analyzing eight SOA schemes implemented in five widely used air quality models: CAMx, CMAQ, GEOS-Chem, WRF-Chem and CHIMERE. We performed offline calculations to compare initial SOA yields, the effects of SOA aging processes, and the influence of NOx conditions on yields. Our objective is to understand variation rather than to identify a superior scheme. We find significant discrepancies in initial SOA yields leading to different precursor rankings of SOA-forming potential. The ratio of maximum to minimum initial yield spans from 1.8 to over 1000, depending upon precursor, with the median of 4.2 underscoring large uncertainties. The impact of NOx conditions on SOA yields is also highly variable among schemes. While some schemes include SOA aging, their treatments differ substantially, with some schemes showing large increases in SOA mass, while others exhibit minimal changes. The substantial differences among current SOA schemes highlight a lack of consensus within the air quality modelling community. Evaluating model simulation results using ambient measurements is unlikely to resolve these discrepancies because uncertainties in SOA formation and precursor emissions are deeply intertwined. The limitations of current SOA schemes should be recognized and acknowledged because model choice can greatly influence predicted SOA concentrations and their evolution, ultimately impacting air quality forecasts, assessments, and regulatory decisions.

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Published
2025-08-20
DOI
https://doi.org/10.5194/egusphere-2025-3921
Primary Topic
Toxic Organic Pollutants Impact
Type
article
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article

Comparing Secondary Organic Aerosols Schemes Implemented in Current Chemical Transport Models and the Policy Implications of Uncertainties

Pradeepa Vennam, Katie Tuite, Ling Huang, Ziang Wu et al.
Toxic Organic Pollutants Impact
article

Comparing Secondary Organic Aerosols Schemes Implemented in Current Chemical Transport Models and the Policy Implications of Uncertainties

Pradeepa Vennam, Katie Tuite, Ling Huang, Ziang Wu, Greg Yarwood, Benjie Chen, Li Li
article en

Abstract

Abstract. Secondary organic aerosol (SOA) constitutes a major component of fine particulate matter (PM2.5) that models must account for to assess how human activities influence air quality, climate, and public health. We characterize the current state of SOA modeling by analyzing eight SOA schemes implemented in five widely used air quality models: CAMx, CMAQ, GEOS-Chem, WRF-Chem and CHIMERE. We performed offline calculations to compare initial SOA yields, the effects of SOA aging processes, and the influence of NOx conditions on yields. Our objective is to understand variation rather than to identify a superior scheme. We find significant discrepancies in initial SOA yields leading to different precursor rankings of SOA-forming potential. The ratio of maximum to minimum initial yield spans from 1.8 to over 1000, depending upon precursor, with the median of 4.2 underscoring large uncertainties. The impact of NOx conditions on SOA yields is also highly variable among schemes. While some schemes include SOA aging, their treatments differ substantially, with some schemes showing large increases in SOA mass, while others exhibit minimal changes. The substantial differences among current SOA schemes highlight a lack of consensus within the air quality modelling community. Evaluating model simulation results using ambient measurements is unlikely to resolve these discrepancies because uncertainties in SOA formation and precursor emissions are deeply intertwined. The limitations of current SOA schemes should be recognized and acknowledged because model choice can greatly influence predicted SOA concentrations and their evolution, ultimately impacting air quality forecasts, assessments, and regulatory decisions.

Shanghai University (CN), Marin Community Foundation (US)
Electric Power Research Institute, National Natural Science Foundation of China
Openalex Percentile: Top 72%
Toxic Organic Pollutants Impact
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