REMOTE SENSING OF AEROSOL AND THE PLANETARY BOUNDARY LAYER, AND EXPLORING THEIR INTERACTIONS

Aerosol-planetary boundary layer (PBL) interaction (API) is an important mechanism affecting the thermodynamics and convection in the lower atmosphere. API plays a critical role in the formation of severe pollution events and the development of convective clouds. Despite the progress made in understanding these processes, their magnitude and significance still have large uncertainties, varying significantly with aerosol distribution, aerosol optical property, and meteorological conditions. This study attempts to develop advanced remote sensing algorithms to retrieve information about the PBL and the aerosols contained within it. These remote sensing techniques are further used to elucidate the mechanisms governing API, enhancing our ability to predict air quality and model convective clouds, as well as understand the impact of aerosols on the climate system.In particular, we develop algorithms to improve the retrieval accuracy of aerosols and the PBL from satellite sensors and a ground-based lidar. For aerosol remote sensing, we use the deep neural network (DNN) to construct surface reflectance relationships (SRR) between different wavelengths. We then incorporate the DNN-constrained SRR into a traditional dark-target algorithm to retrieve the aerosol optical depth (AOD) using information from a current-generation geostationary satellite, i.e., Himawari-8, as input. As a result, the performance of AOD retrievals over East Asia is significantly improved. For PBL remote sensing, we explore different techniques for retrieving the PBL height (PBLH) from both a space-borne lidar (i.e., the Cloud-Aerosol Lidar with Orthogonal Polarization) and a ground-based lidar. We further develop a new method that combines lidar-measured aerosol backscatter with a stability-dependent model of PBLH diurnal variation. The new method circumvents or alleviates an inherent limitation of lidar-based PBLH detection when a residual layer of aerosols does not change in phase with the evolving thermodynamics. By separately considering surface-cloud coupling regimes, this method also offers high-quality retrievals of PBLH under cloudy conditions. Utilizing the enhanced retrievals of PBLH and synergistic measurements, we can also address some scientific questions concerning API, including the influencing factors of API and the role of aerosol vertical distributions. The correlation between the PBLH and the concentration of particulate matter with aerodynamic diameters less than 2.5 microns is generally negative. However, the magnitude, significance, and even the sign of their relationship vary greatly, depending on location and meteorological and aerosol conditions. In particular, API is considerably different under three aerosol vertical structure scenarios (i.e., well-mixed, decreasing and increasing with height). The vertical distribution of aerosol radiative forcing differs dramatically among the three types, with strong heating in the lower, middle, and upper PBL, respectively. Such a discrepancy in aerosol radiative forcing leads to different aerosol effects on atmospheric stability and entrainment processes. Absorbing aerosols are much less effective in stabilizing the lower atmosphere when aerosols decrease with height than in an inverted structure scenario

Climate Change and Air Pollution Relationships. Lessons from a Subtropical Desert Region

The Atacama Desert is the dryest desert on Earth. Atmospheric, ocean, and topographic forcings preserve an exceptional hyper-arid environment. As a product of anthropogenic and natural emissions, PM10 and PM2.5 atmospheric concentrations have been observed to exceed international standards in urban areas where about 1.5 million people live. This research starts by describing the climate dynamics in northern Chile along with the primary anthropogenic emission sources of PM10, PM2.5, and gaseous precursor pollutants. Then, air quality levels across urban areas are evidenced. As a major source of natural PM, the unexplored mineral dust cycle of the Atacama desert is studied from satellite retrievals of aerosols properties. Two areas in the Antofagasta region are identified as predominant sources of dust, where links with reanalysed wind patterns are reported. This study is followed by the analysis of the relationship between PM10-PM2.5 levels and atmospheric ventilation from observational and modelled datasets. Because of the significant link found between both, especially in coastal areas, a wheater-driven model for PM events, with atmospheric ventilation as the most significant input variable, is pro- posed for the coastal city of Antofagasta. Finally, the future of the Atacama Desert, comprising atmospheric and oceanic regional forcings and future PM10-PM2.5 levels, is explored from the UKESM1 model. The South Pacific Anticyclone is already extending and intensifying during the austral summertime. The above leads to increasing upwelling-favourable winds and coastal upwelling intensity of the Humboldt system at the surface ocean, enhancing atmospheric stability. However, a decline is simulated at deeper ocean layers. PM10-PM2.5 are both projected to increase under the SSP370 and SSP585 climate change experiments during the 21st Century. This increasing trend is more abrupt under the SSP370 than the SSP585 experiment due to increased SO2 and dust emissions and the absence of mitigation measurements. Policy implications are dis- cussed, and future academic research is proposed, including implications beyond academia