Abstract
Abstract. High concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) in China have caused severe visibility degradation. Accurate simulations of PM2.5 and its chemical components are essential for evaluating the effectiveness of pollution control strategies and the health and climate impacts of air pollution. In this study, we compared the GEOS-Chem model simulations with comprehensive datasets for organic aerosol (OA), sulfate, nitrate, and ammonium in China. Model results are evaluated spatially and temporally against observations. The new OA scheme with a simplified secondary organic aerosol (SOA) parameterization significantly improves the OA simulations in polluted urban areas, highlighting the important contributions of anthropogenic SOA from semivolatile and intermediate-volatility organic compounds. The model underestimates sulfate and overestimates nitrate for most of the sites throughout the year. More significant underestimation of sulfate occurs in winter, while the overestimation of nitrate is extremely large in summer. The model is unable to capture some of the main features in the diurnal pattern of the PM2.5 chemical components, suggesting inaccuracies in the presented processes. Potential model adjustments that may lead to a better representation of the boundary layer height, the precursor emissions, hydroxyl radical concentrations, the heterogeneous formation of sulfate and nitrate, and the wet deposition of nitric acid and nitrate have been tested in the sensitivity analysis. The results show that uncertainties in chemistry perhaps dominate the model biases. The proper implementation of heterogeneous sulfate formation and the good estimates of the concentrations of sulfur dioxide, hydroxyl radical, and aerosol liquid water are essential for the improvement of the sulfate simulation. The update of the heterogeneous uptake coefficient of nitrogen dioxide significantly reduces the modeled concentrations of nitrate. However, the large overestimation of nitrate concentrations remains in summer for all tested cases. The possible bias in the chemical production and the wet deposition of nitrate cannot fully explain the model overestimation of nitrate, suggesting issues related to the atmospheric removal of nitric acid and nitrate. A better understanding of the atmospheric nitrogen budget, in particular, the role of the photolysis of particulate nitrate, is needed for future model developments. Moreover, the results suggest that the remaining underestimation of OA in the model is associated with the underrepresented production of SOA.
Highlights
In developing countries like China and India, the concentrations of PM2.5 often exceed air-quality standards, leading to visibility reduction and negative health effects (Chan and Yao, 2008; Lelieveld et al, 2015)
The underestimation of organic aerosol (OA) and the overestimation of nitrate are present in the studies for the United States and Europe, while the sulfate concentrations are reproduced in those regions (Heald et al, 2012; Drugé et al, 2019; Jiang et al, 2019)
Uncertainties exist in meteorological fields, emission inventories, and the physical and chemical processes, which contribute to the model biases in the PM2.5 simulations
Summary
In developing countries like China and India, the concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) often exceed air-quality standards, leading to visibility reduction and negative health effects (Chan and Yao, 2008; Lelieveld et al, 2015). Model evaluations in China have reached an agreement that the CTMs generally underestimate the concentrations of organic aerosol (OA) (Fu et al, 2012; Han et al, 2016) and sulfate Uncertainties exist in meteorological fields, emission inventories, and the physical and chemical processes, which contribute to the model biases in the PM2.5 simulations. The heterogeneous formation can be simplified in models as a reactive uptake process to achieve a better agreement of sulfate concentrations Substantial model– observation discrepancies are present in the comparisons of the mass concentration and the oxidation state of OA as well as the contributions of various formation pathways (Tsigaridis et al, 2014; Heald et al, 2011; Chen et al, 2015). Sensitivity analyses were conducted for two case periods to evaluate the contributions of the individual potential factors to the model–observation gaps and the contributions of various combinations of these factors
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