Modeling and Forecasting Impacts of Urban Canopy on New York City Air Quality

Addressing heightened ozone levels that go beyond health-related air quality benchmarks remains a critical concern, especially for populated cities near coastlines. Despite accounting for less than 10% of the land area in the United States (US), coastal shoreline counties contain more than 40% of the population. In these areas, urban expansion significantly transforms local atmospheric and surface features, leading to changes in air pollutant distribution patterns. Such shifts add layers of complexity to the already challenging task of accurate air quality prediction. This study assesses the performance of a real-time air quality forecast model, placing particular emphasis on the intricate relationship between urban meteorology and chemical transport over New York City. Furthermore, we delve into the temporal and spatial evolution of the urban boundary layer during the summer of 2023, supporting the efforts of the Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) field campaign. A high-resolution configuration of the Weather Research and Forecasting (WRF) model was used, where the chemistry and meteorology formulations were fully coupled using an advanced multilayer urban canopy model (uWRF - Chem). This system was configured to provide a daily forecast in the summer of 2023 and produces daily 48-hr forecast. Other key model features include the use of an improved planetary boundary layer scheme that links the Mellor-Yamada-Nakanishi-Niino (MYNN) Eddy Diffusivity and Mass Flux (EDMF) scheme with the multi-layer Building Environment Parameterization (BEP) scheme. It also includes inline non-local mixing of chemical species. Preliminary results suggest that the model can capture complex urban surface influence on land-sea breezes and PBL dynamics (i.e. building-drag retardation on momentum and thermal anthropogenic heat influences), and in turn, how urban and coastal meteorology affects NO2 spatial distribution and ozone generation in densely populated and industrialized cities. Our results further support the adoption of regional urbanized air quality models for real-time air quality forecasts.