Mesoscale modeling study of the interactions between aerosols and PBL meteorology during a haze episode in Jing–Jin–Ji (China) and its nearby surrounding region – Part 1: Aerosol distributions and meteorological features

Abstract

Abstract. The urbanized region ofJing(Beijing)-Jin(Tianjin)-Ji (alias of Hebei province) and its nearby surrounding region (3JNS) is becoming China's most polluted area by haze, exceeding even the Yangtze and Pearl river deltas. Aside from pollutant emission, the meteorology of the planetary boundary layer (PBL) is the most important factor affecting haze pollution. Focusing on July 2008, the aerosol optical properties and PBL meteorology features closely related to haze formation were simulated in the 3JNS region using an online atmospheric chemical transport model. The relationship between regional PBL meteorology, PM 2.5 , and haze is discussed. Model results accurately simulated the aerosol optical depth (AOD), single scattering albedo (SSA) and asymmetry parameter (ASY), validated by comparison with observations from the MODerate Resolution Imaging Spectroradiometer (MODIS), the China Aerosol Remote Sensing NETwork (CARSNET) and the Aerosol Robotic NETwork (AERONET). Modeled PBL wind speeds showed reasonable agreement with those from the National Centers for Environmental Prediction (NCEP) Reanalysis 2. A monthly mean AOD value as high as 1.2 was found from both model and observations, with a daily mean larger than 2.0 during haze episodes in the 3JNS region. Modeled and observed SSA values of 0.90-0.96 and ASY values of 0.72-0.74 demonstrated the high scattering characteristic of summer aerosols in this region. PBL wind speeds from modeled and NCEP data both showed a reversing trend of PM 2.5 variation, illustrating the importance of the "PBL window shadow" in haze formation. Turbulence diffusion and PBL height had opposite phases to surface PM 2.5 , indicating that lower PBL height and weaker PBL turbulence diffusion are essential to haze formation. It is noted that homogeneous air pressure does not occur at the surface, but at an 850-950 hPa height during the haze episode. The momentum transmitting downward of the cold air from above the PBL to the low PBL and surface lead to an increase in surface wind speeds and haze dispersal.

Mesoscale modelling study of the interactions between aerosols and PBL meteorology during a haze episode in China Jing–Jin–Ji and its near surrounding region – Part 2: Aerosols' radiative feedback effects

“…The control (CTL) experiment is the base simulation without calculating aerosol radiative feedback and impacts online as described in Part 1 (Wang et al, 2015). In this paper, the simulation experiment (online active interacting meteorologyaerosol-radiation) is referred to as the RAD experiment.…”

“…The dynamic core, physics processes option, chemical frame including emission sources, gas and aerosol processes, and interaction between gas and aerosols in the GRAPES/CUACE model have been introduced in Part 1 (Wang et al, 2015). This section provides a brief description of the radiative transfer scheme used in this research.…”

“…Aerosol optical depth (AOD) (τ a ), single scattering albedo (ω a ) and Asymetry factor (g a ) are calculated by an external mixing scheme of different types of aerosols as described in the companion paper (Part 1, Wang et al, 2015). The effect of aerosols on solar and thermal radiation within the GRAPES/CUACE model is realized by implementing τ a , ω a and g a into the CLIRAD radiation scheme.…”

“…Focusing on July 2008 and a haze episode from 7 to 11 July in 3JNS, an external mixing scheme of seven kinds of aerosols has been introduced into the GRAPES/CUACE model to evaluate the optical features of composite aerosols and discuss PBL aerosol loading, the PBL meteorological properties closely related to haze and their relationship to haze episodes (Part 1 of the companion paper, Wang et al, 2015). In this article, the aerosol optical properties are used as input parameters in a radiative transfer scheme where the radiative heating rates are fed back to the online dynamic frame of the GRAPES/CUACE.…”

Inverse modeling of black carbon emissions over China using ensemble data assimilation

“…NCEP 1 • ×1 • reanalysis data are employed for the model's initial and 6 h meteorological lateral boundary input field and forecast time is every 24 h throughout every month to ensure the model's fair ability to simulation of meteorological field (Wang et al, 2015). The monthly mean of simulated BC is put into the equation as C, and the y also uses the monthly mean of the BC observations.…”