Land-atmosphere Exchange and Air Quality during Stable Atmospheric Boundary Layer Events
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Elevated air pollution concentrations have been observed under conditions with stable atmospheric boundary layers. The multiday stagnant meteorological conditions, especially the vertical structure of the atmospheric boundary layer (ABL) below 1 km in the atmosphere, have been notoriously difficult to capture using numerical weather prediction (NWP) models. The land-atmosphere exchange processes control the energy exchange at the interface of the surface and atmosphere, which impacts the ABL development. Thus, well-represented land-atmosphere exchange in numerical models is a perquisite for reliable meteorological predictability. A need for additional observations and numerical experiments focusing on the land-atmosphere exchange has been identified with the aim to improve NWP models and thus air quality modeling under stable ABL conditions. Persistent cold air pool (PCAP) events are accompanied by a stably stratified atmosphere and limited mixing and can lead to an accumulation of air pollution in valleys during winter. This dissertation analyzes the surface turbulent characteristics from observations and evaluates the numerical model performances using the Weather Research and Forecasting (WRF) model and the Community Multiscale Air Quality Modeling (CMAQ) System. The objective of this research is to investigate the land-atmosphere exchanges and air pollution concentrations during PCAPs, where a case study for the surface turbulent fluxes over rolling terrain is conducted first to investigate the WRF model sensitivity to land-use datasets, large-scale forcing datasets, and physics schemes. The findings from this first study in rolling terrain were used in model sensitivity runs to investigate the influence of boundary layer and land surface physics schemes on the model results for mountainous terrain during winter.Suppressed surface turbulence with lower magnitudes of sensible (H) and latent (LE) heat fluxes are observed during strong PCAP events compared with non-PCAPs. The surface turbulent fluxes are impacted by net radiation (Rn), PCAP scenario (PCAP or non-PCAP), as well as the CAP type (cloudy or dry). Dynamic land use information is needed in numerical models considering the spatial variations of surface exchange coefficient. The significantly overestimated H and LE in WRF is related to overestimated surface exchange coefficient (CH) and soil moisture. The underestimation of non-dimensional vertical gradient for temperature in stability functions based on the Monin-Obukhov similarity theory is responsible for the CH discrepancies. Numerical sensitivity experiments show that there is no one WRF configuration that performs best for all meteorology variables (temperature, wind speed, surface turbulent fluxes) and under all conditions (day and time, stable and unstable). The temporal variability of the elevated air pollution concentrations during PCAPs is captured by the CMAQ model, but CMAQ underestimates the magnitudes. Underestimation of the valley heat deficit accompanied by more vertical mixing in the model simulations contributes to the underestimation of PM2.5 concentrations compared with observations. This research highlights the need to develop new flux-profile relationships under stable conditions over complex terrain to improve the land-atmosphere exchange simulated in atmospheric models and the importance of meteorology uncertainties that contribute to air quality modeling deficiencies during PCAP events.