Filterable and Condensable Particulate Nitrate Emissions from Plumes over North China.

Area of Science:

• Atmospheric Chemistry
• Environmental Science
• Air Quality Modeling

Background:

• Particulate nitrate (NO3-) in North China is often underestimated by chemical transport models (CTMs).
• A persistent low bias in models suggests a missing source of NO3-.

Purpose of the Study:

• To quantify plume primary NO3- (P-NO3-), including filterable and condensable fractions, in North China.
• To investigate the contribution of condensable particulate matter (CPM) to P-NO3- emissions.
• To improve the accuracy of air quality models by incorporating a missing NO3- source.

Main Methods:

• Integrated a sector-specific emissions framework with oxygen-isotope constraints and WRF-CMAQ simulations.
• Compiled a China-specific source-profile database for filterable P-NO3-.
• Constructed a comprehensive CPM inventory across nine anthropogenic sectors.
• Applied a Bayesian isotope model (δ18O) to determine P-NO3- contributions.

Main Results:

• Plume P-NO3- emissions were dominated by the condensable fraction (91.5%) and industrial/power sources (92.5%).
• Incorporating CPM into CMAQ increased near-surface P-NO3- by 4.6-10.1%, improving model performance.
• Oxygen-isotope analysis indicated P-NO3- contributions of 4.5-13.1% and highlighted model overestimation of the NO3- to ·OH+NO2 pathway when this source was omitted.

Conclusions:

• Condensable particulate matter (CPM)-driven plume P-NO3- represents a significant missing source in North China.
• Explicit representation of CPM-driven P-NO3- is crucial for accurate air quality inventories, CTMs, and NO3- mitigation strategies.