New Multiphase Chemical Processes Influencing Atmospheric Aerosols, Air Quality, and Climate in the Anthropocene
Hang Su, Yafang Cheng, Ulrich Pöschl
Abstract
observed during haze events, suggesting a gap in our understanding of the chemical mechanisms of aerosol formation. These haze events are characterized by high concentrations of aerosol particles and high humidity, especially favoring multiphase chemistry. In this Account, we review recent advances that we have made, as well as current challenges and future perspectives for research on multiphase chemical processes involved in atmospheric aerosol formation and transformation. We focus on the following questions: what are the key reaction pathways leading to aerosol formation under polluted conditions, what is the relative importance of multiphase chemistry versus gas-phase chemistry, and what are the implications for the development of efficient and reliable air quality control strategies? In particular, we discuss advances and challenges related to different chemical regimes of sulfate, nitrate, and secondary organic aerosols (SOAs) under haze conditions, and we synthesize new insights into the influence of aerosol water content, aerosol pH, phase state, and nanoparticle size effects. Overall, there is increasing evidence that multiphase chemistry plays an important role in aerosol formation during haze events. In contrast to the gas phase photochemical reactions, which are self-buffered against heavy pollution, multiphase reactions have a positive feedback mechanism, where higher particle matter levels accelerate multiphase production, which further increases the aerosol concentration resulting in a series of record-breaking pollution events. We discuss perspectives to fill the gap of the current understanding of atmospheric multiphase reactions that involve multiple physical and chemical processes from bulk to nanoscale and from regional to global scales. A synthetic approach combining laboratory experiments, field measurements, instrument development, and model simulations is suggested as a roadmap to advance future research.