2021 journal article
Partitioning of NH3-NH4+ in the Southeastern U.S.
Atmosphere.
author keywords: inorganic PM; (2 5); precursor gas; thermodynamic equilibrium modeling
open access via www.mdpi.com (publisher PDF)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
11. Sustainable Cities and Communities
(Web of Science)
13. Climate Action
(Web of Science)
Source: ORCID
Added: December 16, 2021
The formation of inorganic fine particulate matter (i.e., iPM2.5) is controlled by the thermodynamic equilibrium partitioning of NH3-NH4+. To develop effective control strategies of PM2.5, we aim to understand the impacts of changes in different precursor gases on iPM2.5 concentrations and partitioning of NH3-NH4+. To understand partitioning of NH3-NH4+ in the southeastern U.S., responses of iPM2.5 to precursor gases in four seasons were investigated using field measurements of iPM2.5, precursor gases, and meteorological conditions. The ISORROPIA II model was used to examine the effects of changes in total ammonia (gas + aerosol), total sulfuric acid (aerosol), and total nitric acid (gas + aerosol) on iPM2.5 concentrations and partitioning of NH3-NH4+. The results indicate that reduction in total H2SO4 is more effective than reduction in total HNO3 and total NH3 to reduce iPM2.5 especially under NH3-rich condition. The reduction in total H2SO4 may change partitioning of NH3-NH4+ towards gas-phase and may also lead to an increase in NO3− under NH3-rich conditions, which does not necessarily lead to full neutralization of acidic gases (pH < 7). Thus, future reduction in iPM2.5 may necessitate the coordinated reduction in both H2SO4 and HNO3 in the southeastern U.S. It is also found that the response of iPM2.5 to the change in total H2SO4 is more sensitive in summer than winter due to the dominance of SO42− salts in iPM2.5 and the high temperature in summer. The NH3 emissions from Animal Feeding Operations (AFOs) at an agricultural rural site (YRK) had great impacts on partitioning of NH3-NH4+. The Multiple Linear Regression (MLR) model revealed a strong positive correlation between cation-NH4+ and anions-SO42− and NO3−. This research provides an insight into iPM2.5 formation mechanism for the advancement of PM2.5 control and regulation in the southeastern U.S.