Study of atmospheric aerosols and mixing layer by LIDAR

Insights into multidimensional transport flux from vertical observation and numerical simulation in two cities in North China

This study represents the first quantitative evaluation of pollution transport budget within the boundary layer of typical cities in the Beijing-Tianjin-Hebei (BTH) region from the perspective of horizontal and vertical exchanges and further discusses the impact of the atmospheric boundary layer (ABL)-free troposphere (FT) exchange on concentration of fine particulate matter (PM_2.5) within the ABL during heavy pollution. From the perspective of the transport flux balance relationship, differences in pollution transport characteristics between the two cities is mainly reflected in the ABL-FT exchange effect. The FT mainly flowed into the ABL in BJ, while in SJZ, the outflow from the ABL to the FT was more intense. Combined with an analysis of vertical wind profile distribution, BJ was found to be more susceptible to the influence of northwest cold high prevailing in winter, while sinking of strong cold air allowed the FT flowing into the ABL influence the vertical exchange over BJ. In addition, we selected a typical pollution event for targeted analysis to understand mechanistic details of the influence of ABL-FT exchange on the pollution event. These results showed that ABL-FT interaction played an important role in PM_2.5 concentration within the ABL during heavy pollution. Especially in the early stage of heavy pollution, FT transport contributed as much as 82.74% of PM_2.5 within the ABL. These findings are significant for improving our understanding of pollution transport characteristics within the boundary layer and the effect of ABL-FT exchange on air quality.

Retrieval of the planetary boundary layer height from lidar measurements by a deep-learning method based on the wavelet covariance transform

Understanding and characterization of the planetary boundary layer (PBL) are of great importance in terms of air pollution management, weather forecasting, modelling of climate change, etc. Although many lidar-based approaches have been proposed for the retrieval of the PBL height (PBLH) in case studies, development of a robust lidar-based algorithm without human intervention is still of great challenging. In this work, we have demonstrated a novel deep-learning method based on the wavelet covariance transform (WCT) for the PBLH evaluation from atmospheric lidar measurements. Lidar profiles are evaluated according to the WCT with a series of dilation values from 200 m to 505 m to generate 2-dimensional wavelet images. A large number of wavelet images and the corresponding PBLH-labelled images are created as the training set for a convolutional neural network (CNN), which is implemented based on a modified VGG16 (VGG - Visual Geometry Group) convolutional neural network. Wavelet images obtained from lidar profiles have also been prepared as the test set to investigate the performance of the CNN. The PBLH is finally retrieved by evaluating the predicted PBLH-labelled image and the wavelet coefficients. Comparison studies with radiosonde data and the Micro-Pulse-Lidar Network (MPLNET) PBLH product have successfully validated the promising performance of the deep-learning method for the PBLH retrieval in practical atmospheric sensing.

Vertical distribution of hydrocarbons in the low troposphere below and above the mixing height: tethered balloon measurements in Milan, Italy

A novel approach for measuring vertical profiles of HCs and particle number concentrations was described and applied in the low troposphere over Milan (Italy) during typical spring and summer days. Particle profiles yielded nearly homogeneous concentrations below the mixing height, with level-to-ground concentration ratios of 92-97%, while HCs showed a more pronounced decrease (74-95%). Vertical mixing and photochemical loss of HCs were demonstrated to cause these gradients. Much lower concentrations were observed for the profiles above the mixing height, where the HC mixtures showed also a different composition, which was partially explained by the horizontal advection of air with HC sources different to those prevailing at the site. The application of pseudo-first order kinetics for reactions between HCs and the hydroxyl radical allowed for the estimation of the vertical mixing time scale in the order of 100 ± 20 min.

Investigation of the 3-D actinic flux field in mountainous terrain

During three field campaigns spectral actinic flux was measured from 290-500 nm under clear sky conditions in Alpine terrain and the associated O3- and NO2-photolysis frequencies were calculated and the measurement products were then compared with 1-D- and 3-D-model calculations. To do this 3-D-radiative transfer model was adapted for actinic flux calculations in mountainous terrain and the maps of the actinic flux field at the surface, calculated with the 3-D-radiative transfer model, are given. The differences between the 3-D- and 1-D-model results for selected days during the campaigns are shown, together with the ratios of the modeled actinic flux values to the measurements. In many cases the 1-D-model overestimates actinic flux by more than the measurement uncertainty of 10%. The results of using a 3-D-model generally show significantly lower values, and can underestimate the actinic flux by up to 30%. This case study attempts to quantify the impact of snow cover in combination with topography on spectral actinic flux. The impact of snow cover on the actinic flux was ~ 25% in narrow snow covered valleys, but for snow free areas there were no significant changes due snow cover in the surrounding area and it is found that the effect snow-cover at distances over 5 km from the point of interest was below 5%. Overall the 3-D-model can calculate actinic flux to the same accuracy as the 1-D-model for single points, but gives a much more realistic view of the surface actinic flux field in mountains as topography and obstruction of the horizon are taken into account.

Vertical profiles of aerosol absorption coefficient from micro-Aethalometer data and Mie calculation over Milan

Vertical profiles of aerosol number-size distribution and black carbon (BC) concentration were measured between ground-level and 500m AGL over Milan. A tethered balloon was fitted with an instrumentation package consisting of the newly-developed micro-Aethalometer (microAeth® Model AE51, Magee Scientific, USA), an optical particle counter, and a portable meteorological station. At the same time, PM(2.5) samples were collected both at ground-level and at a high altitude sampling site, enabling particle chemical composition to be determined. Vertical profiles and PM(2.5) data were collected both within and above the mixing layer. Absorption coefficient (b(abs)) profiles were calculated from the Aethalometer data: in order to do so, an optical enhancement factor (C), accounting for multiple light-scattering within the filter of the new microAeth® Model AE51, was determined for the first time. The value of this parameter C (2.05±0.03 at λ=880nm) was calculated by comparing the Aethalometer attenuation coefficient and aerosol optical properties determined from OPC data along vertical profiles. Mie calculations were applied to the OPC number-size distribution data, and the aerosol refractive index was calculated using the effective medium approximation applied to aerosol chemical composition. The results compare well with AERONET data. The BC and b(abs) profiles showed a sharp decrease at the mixing height (MH), and fairly constant values of b(abs) and BC were found above the MH, representing 17±2% of those values measured within the mixing layer. The BC fraction of aerosol volume was found to be lower above the MH: 48±8% of the corresponding ground-level values. A statistical mean profile was calculated, both for BC and b(abs), to better describe their behaviour; the model enabled us to compute their average behaviour as a function of height, thus laying the foundations for valid parametrizations of vertical profile data which can be useful in both remote sensing and climatic studies.