Sulfate formation during heavy winter haze events and the potential contribution from heterogeneous SO₂ + NO₂ reactions in the Yangtze River Delta region, China

• Main Authors: L. Huang, J. An, B. Koo, G. Yarwood, R. Yan, Y. Wang, C. Huang, L. Li
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-11-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/19/14311/2019/acp-19-14311-2019.pdf

<p>Rapid sulfate formation is recognized as a key characteristic of severe winter haze in China. However, air quality models tend to underestimate sulfate formation during heavy haze periods, and heterogeneous formation pathways have been proposed as promising mechanisms to reduce gaps between observation and model simulation. In this study, we implemented a reactive <span class="inline-formula">SO₂</span> uptake mechanism through the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions in the Comprehensive Air Quality Model with Extensions (CAMx) to improve simulation of sulfate formation in the Yangtze River Delta (YRD) region. Parameterization of the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions is based on observations in Beijing and considered both the impact of relative humidity and aerosol pH on sulfate formation. Ammonia is reported to be critical for the formation of secondary inorganic aerosols. Estimation of ammonia emissions is usually associated with large uncertainties and models tend to underestimate ammonia concentrations substantially. Sensitivity tests were conducted to evaluate the influence of the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions as well as ammonia emissions on modeled sulfate concentrations during a period with several heavy haze episodes in the YRD region. Base case model results show large underestimation of sulfate concentrations by 36&thinsp;% under polluted conditions in the YRD region. Adding the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions or doubling ammonia emissions alone leads to slight model improvement (<span class="inline-formula">∼6</span>&thinsp;%) on simulated sulfate concentrations in the YRD region. However, model performance significantly improved when both the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions and doubled ammonia emissions were included in the simulation: predicted sulfate concentrations during polluted periods increased from 23.1&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula">⁻³</span> in the base scenario to 29.1&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula">⁻³</span> (representing an increase of 26&thinsp;%). Aerosol pH is crucial for the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions, and our calculated aerosol pH is always acidic and increased by 0.7 with doubled ammonia emissions. Modeling results also show that this reactive <span class="inline-formula">SO₂</span> uptake mechanism enhanced sulfate simulations by 1 to 5&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula">⁻³</span> for the majority of the eastern and central parts of China, with more than 20&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula">⁻³</span> increase in sulfate concentrations over the northeastern plain. These findings suggest that the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions could be potentially important for sulfate formation in the YRD region as well as other parts of China. Further studies are needed to constrain the uncertainties associated with the parameterization of the <span class="inline-formula">SO₂+NO₂</span> heterogeneous reactions based on local data as well as to evaluate this mechanism in other regions. In addition, ammonia emissions were found to be a key driving variable of the spatial patterns of sulfate enhancement due to the new pathway. Substantial efforts are needed to improve the accuracy of the ammonia emission inventory.</p>