摘要

Evaluations of air pollutants and trace gas measurements over mountaintop sites and their application in inverse transport models to estimate regional scale fluxes are oftentimes challenging due to the influences associated with atmospheric transport at both local and regional scales. The objective of this study is to investigate the diurnal cycle pattern of CO mixing ratio over a low mountaintop influenced by: (1) two different convective boundary layer (CBL) regimes (shallow and deep) and associated growth rates over the mountaintop, (2) the combined effect of a deep CBL with and without diurnal wind shift, and (3) slope flows and associated air mass transport. For this purpose, we used simultaneous measurements of lidar-derived CBL heights, standard meteorological variables, and CO2 and CO mixing ratio from Pinnacles, a mountaintop monitoring site in the Appalachian Mountains. We used both water vapor and CO2 mixing ratio as tracers for upslope flow air masses. We used case studies to focus on two different scenarios of daytime CO mixing ratio variability: (1) a gradual increase in the morning with a maximum in the afternoon, and (2) a gradual decrease in the morning with a minimum in the late afternoon. The second scenario is similar to the CO variability observed atop tall towers in flat terrain. Using the lidar-derived CBL height evolution and in situ CO, CO2 and meteorological measurements over the mountaintop, we found that the CBL height dynamics, regional scale wind shift, and upslope flow air masses arriving at the mountaintop in the morning affect the CO mixing ratio variability during the remaining part of the diurnal cycle. These findings help introduce a conceptual framework that can explain and differentiate the opposite patterns (i.e. daytime increase versus daytime decrease) in the CO diurnal cycles over a mountaintop site affected by upslope flows and provide new roadmaps for monitoring and assimilating trace gas mixing ratios into applications requiring regionally-representative measurements.

  • 出版日期2017-9