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Predicted impacts of heterogeneous chemical pathways on particulate sulfur over the N. Hemisphere and Fairbanks, Alaska
Citation:
Farrell, S., H. Pye, R. Gilliam, G. Pouliot, D. Huff, G. Sarwar, W. Vizuete, AND K. Fahey. Predicted impacts of heterogeneous chemical pathways on particulate sulfur over the N. Hemisphere and Fairbanks, Alaska. International Technical Meeting On Air Pollution Modeling And Its Application, Chapel Hill, NC, May 22 - 26, 2023.
Impact/Purpose:
Fairbanks, Alaska is a Serious nonattainment area for the 24-hour PM2.5 National Ambient Air Quality Standard (NAAQS). Violations of the NAAQS typically occur in winter when the cold conditions are associated with strong temperature inversions and air stagnation. This leads to a buildup of particulate pollution at the surface, exacerbated by elevated emissions from residential wood combustion. While the particulate matter composition is dominated by organic carbon, sulfate is the second-largest contributor to particle mass. Mechanisms leading to high sulfate concentrations during cold and dark conditions, when the globally dominant aqueous and gas-phase photochemical SO2 oxidation pathways are limited, remain uncertain. In addition, these conditions may also favor the formation of hydroxymethanesulfonate (HMS), an organosulfur species which is included in certain sulfate measurements (e.g., Moch et al., 2018). While most current chemical transport models include gas-phase oxidation of SO2 by OH and in-cloud aqueous oxidation (e.g., via H2O2 and O3) leading to sulfate, there are conditions, such as those characteristic of Fairbanks winters, where these pathways do not reproduce the high sulfate concentrations that are observed. Implementation of additional heterogeneous sulfur chemistry in air quality models may ameliorate this model-measurement gap. In this work we implement heterogeneous sulfate and HMS chemistry in the Community Multiscale Air Quality (CMAQ) modeling system and investigate the potential impacts of high ionic strength on kinetic rate expressions and model parameters. With a more complete representation of sulfur chemistry, models like CMAQ can be better equipped to link secondary aerosol concentrations to precursor levels and identify effective pathways to attain air quality goals and protect human and ecosystem health.
Description:
Fairbanks, Alaska, is currently in serious non-attainment of the 24-hour fine particulate matter (PM2.5) National Ambient Air Quality Standard, with mass concentrations reaching over 100 ug/m3 during extreme wintertime particulate pollution episodes characterized by strong temperature inversions, low winds, and high home heating emissions. While the particulate matter composition is dominated by organic carbon and driven by primary home heating emissions, sulfate is the second-largest contributor to particle mass. Mechanisms leading to high sulfate concentrations during cold and dark conditions, when the globally dominant aqueous and gas-phase photochemical SO2 oxidation pathways are limited, remain uncertain. In addition, these conditions may also favor the formation of hydroxymethanesulfonate (HMS), an organosulfur species which is detected in certain sulfate measurements (e.g., Moch et al., 2018). While the Community Multiscale Air Quality (CMAQ) modeling system and most current chemical transport models include gas-phase oxidation of SO2 by OH and in-cloud aqueous oxidation (e.g., via H2O2 and O3) leading to sulfate, there are conditions, such as those characteristic of Fairbanks winters, where these pathways do not reproduce the high sulfate concentrations that are observed (CMAQ sulfate NMB ~ -70% for January-February 2008). Implementation of additional heterogeneous sulfur chemistry in air quality models may ameliorate this model-measurement gap. In this work we implement heterogeneous sulfate and HMS chemistry in CMAQ, version 5.3.3, and investigate the potential impacts of high ionic strength on kinetic rate expressions and model parameters. With a more complete representation of sulfur chemistry, models like CMAQ can be better equipped to link secondary aerosol concentrations to precursor levels and identify effective pathways to attain air quality goals and protect human and ecosystem health.