The role of nitric acid in atmospheric new particle formation
Literature Information
Ling Liu, Hao Li, Haijie Zhang, Jie Zhong, Yang Bai, Maofa Ge, Zesheng Li, Yu Chen, Xiuhui Zhang
Nitric acid, an air pollutant with strong acidity and oxidizability, can be found in considerable quantities in the gas and aerosol phase. Understanding the role of nitric acid in atmospheric new particle formation is essential to study the complicated nucleation mechanism. Using density functional theory combined with the Atmospheric Clusters Dynamic Code (ACDC), the role of nitric acid in the formation of new particles has been investigated under different atmospheric conditions (different precursor concentrations and temperatures). The results show that nitric acid can form clusters with sulfuric acid and ammonia by hydrogen bond or even proton-transfer interactions. The concentrations of clusters involving nitric acid can be comparable with those of sulfuric acid–ammonia-based clusters, considering the thermodynamic stability combined with the realistic atmospheric concentrations of precursors. Within the atmospheric concentration range, nitric acid can enhance the formation rates of sulfuric acid–ammonia clusters, especially at low temperature, low sulfuric acid concentration and high ammonia concentration. In addition, the new particle formation mechanism indicates that nitric acid can contribute to the cluster formation and the role of nitric acid in the cluster formation pathway is as a “bridge” connecting the smaller and larger clusters.
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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.














