On the simulations of aerosol pH in China using WRF-Chem (v4.0): sensitivities of aerosol pH and its temporal variations in haze episodes

Abstract

Abstract. Precise estimation of aerosol pH in chemical transport models (CTMs) is critical to aerosol modeling and thus influencing policy development. We reported WRF-Chem simulated PM2.5 pH over China during a period with heavy haze episodes in Beijing, and explored the sensitivity of the modeled aerosol pH to factors including emissions of nonvolatile cations (NVCs) and NH3, aerosol phase state assumption and heterogeneous production of sulfate. We found default WRF-Chem could predict spatial patterns of PM2.5 pH over China similar to other CTMs, but with generally lower pH values largely due to the underestimates of alkaline species (NVCs and NH3) and the difference in thermodynamic treatments between different models. Increasing NH3 emissions in the model would improve the modeled pH in comparison with offline thermodynamic model calculations of pH constrained by observations. In addition, we found that aerosol phase state assumption and heterogeneous sulfate production are important in aerosol pH predictions for regions with low relative humidity (RH) and high anthropogenic SO2 emissions, respectively. These factors should be better constrained in model simulations of aerosol pH in the future. Analysis of the modeled temporal trend of PM2.5 pH in Beijing over a haze episode revealed a clear decrease in pH from 5.21 ± 0.88 in clean period to 3.56 ± 0.49 in heavily polluted period. The increased acidity in more polluted conditions is largely due to the formation and accumulation of secondary species including sulfuric acid and nitric acid, even though being modified by alkaline species (NVCs, NH3). Our result suggests that NO2 oxidation is unlikely to be important for heterogeneous sulfate production in Beijing haze as the effective pH for NO2 oxidation of S(IV) is at higher pH of ~6.

Role of atmospheric aerosols in severe winter fog over Indo Gangetic Plains of India: a case study

“…The underpredicted secondary aerosols over NWIGP where no fog occurred implies underestimation of formation of aerosols through gas and aerosol chemistry in the model. This underestimation could also be linked to an underestimation of pH in the default MOSAIC scheme (Ruan et al, 2022) which slows the secondary aerosol formation, or an underestimation of the aqueous sulfur oxidation in haze aerosol at > 80% RH before the onset of fog (Acharja et al, 2022), or missing multiphase oxidation processes (Wang et al, 2022). We also observed that AR feedback with aqueous chemistry initiated the fog formation 1-2 hours earlier than the initiation time in the simulation without AR feedback and without aqueous phase chemistry whereas AR feedback alone led to early dissipation of fog.…”