Meteorological and Air Quality Modeling for Hawaii, Puerto Rico, and Virgin Islands.

Area of Science:

• Atmospheric Chemistry and Air Quality Modeling
• Environmental Science
• Meteorology

Background:

• Photochemical transport models are crucial for air quality management but traditionally underrepresented in regions like Hawaii, Puerto Rico, and the Virgin Islands.
• Accurate modeling of meteorology, emissions, chemistry, and deposition is essential for supporting regulatory programs such as the National Ambient Air Quality Standards (NAAQS).

Purpose of the Study:

• To develop and evaluate a photochemical model platform for predicting key air pollutants (O3, PM2.5, regional haze) in Hawaii, Puerto Rico, and the Virgin Islands.
• To assess the model's capability in representing meteorological conditions and air quality for supporting air quality management decisions in these under-modeled regions.

Main Methods:

• Application of the Weather Research and Forecasting (WRF) model for meteorology and the Community Multiscale Air Quality (CMAQ) model for photochemical transport.
• Simulations conducted for the entire year of 2016 at multiple grid resolutions (27, 9, and 3 km) covering the specified regions.
• Model predictions were validated against available surface and upper air meteorological and chemical measurements.

Main Results:

• The model accurately represented the vertical gradients of temperature, humidity, and winds in the troposphere.
• Performance for surface meteorology was variable, with temperature underestimation noted in Hawaii. Daily average PM2.5 was generally well characterized.
• Model performance for hourly pollutants (SO2, NO2, PM2.5, CO) was mixed and influenced by emission inventory accuracy and wildfire impacts. Volcanic SO2 emissions were not included and led to underprediction.

Conclusions:

• The developed photochemical modeling system provides a valuable tool for air quality assessment in Hawaii, Puerto Rico, and the Virgin Islands.
• Further research is recommended to improve emission inventory representation and understand the impact of complex land-water and terrain interfaces on microscale meteorology and model performance at higher temporal resolutions.