Improvements of Simulating Urban Atmospheric CO2 Concentration by Coupling with Emission Height and Dynamic Boundary Layer Variations in WRF-STILT Model

Abstract

Although cities only account for 3% of the global land area, they have disproportionately contributed 70% of total anthropogenic CO2 emissions; the main issue in estimating urban anthropogenic CO2 emissions is their large uncertainty. Tower-based atmospheric CO2 observations and simulations in urban areas have been frequently used as an independent approach to constrain and evaluate greenhouse gas emissions from city to regional scales, where only daytime CO2 observations and simulations are used considering the consensus that the large bias in simulating nighttime planetary boundary layer heights (PBLH) and atmospheric CO2 concentration will cause overestimation/underestimation in CO2 emission inversions. The above strategy of only using daytime observations makes the numbers of available concentration observations largely decrease even with the fact that tower-based atmospheric CO2 observations are sparsely distributed and conducted. Here, to solve the issue of large bias in nighttime CO2 simulations, we conducted four months of atmospheric CO2 observations from January to April in 2019, and raised an approach by coupling emission heights with dynamic PBLH variations in a WRF-STILT model. We found (1) the overestimation of simulated nighttime CO2 concentration decreased by 5–10 ppm, especially between 0:00 and 7:00. (2) The statistics for nighttime simulations were largely improved by using a revised model and posteriori emissions. The regression slopes of daily averages were 0.93 and 0.81 for the default model using a priori emissions and the revised model using the same a priori emissions, and the slope largely improved to 0.97 for the revised model using posteriori emissions. Moreover, the correlation coefficient also increased from 0.29 and 0.37 to 0.53; these results indicate our revised model obviously calibrated the bias in both nighttime and daily CO2 concentration simulations. In general, it is strongly recommended to use the revised WRF-STILT model in future inversion studies, which can effectively reduce the overestimation of nighttime spikes and make full use of nighttime observations.