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

ABSTRACT: A photochemical model platform for Hawaii, Puerto Rico, and Virgin Islands predicting O₃, PM_2.5, and regional haze would be useful to support assessments relevant for the National Ambient Air Quality Standards (NAAQS), Regional Haze Rule, and the Prevention of Significant Deterioration (PSD) program. These areas have not traditionally been modeled with photochemical transport models, but a reasonable representation of meteorology, emissions (natural and anthropogenic), chemistry, and deposition could support air quality management decisions in these areas. Here, a prognostic meteorological model (Weather Research and Forecasting) and photochemical transport (Community Multiscale Air Quality) model were applied for the entire year of 2016 at 27, 9, and 3 km grid resolution for areas covering the Hawaiian Islands and Puerto Rico/Virgin Islands. Model predictions were compared against surface and upper air meteorological and chemical measurements available in both areas. The vertical gradient of temperature, humidity, and winds in the troposphere was well represented. Surface layer meteorological model performance was spatially variable, but temperature tended to be underestimated in Hawaii. Chemically speciated daily average PM_2.5 was generally well characterized by the modeling system at urban and rural monitors in Hawaii and Puerto Rico/Virgin Islands. Model performance was notably impacted by the wildfire emission methodology. Model performance was mixed for hourly SO₂, NO₂, PM_2.5, and CO and was often related to how well local emissions sources were characterized. SO₂ predictions were much lower than measurements at monitors near active volcanos on Hawaii, which was expected since volcanic emissions were not included in these model simulations. Further research is needed to assess emission inventory representation of these areas and how microscale meteorology influenced by the complex land-water and terrain interfaces impacts higher time resolution performance.

SUBMITTER: Baker KR 

PROVIDER: S-EPMC7322826 | biostudies-literature |

REPOSITORIES: biostudies-literature