Analysis of Atmospheric Aerosol Optical Properties in the Northeast Brazilian Atmosphere with Remote Sensing Data from MODIS and CALIOP/CALIPSO Satellites, AERONET Photometers and a Ground-Based Lidar

A 12-year analysis, from 2005 to 2016, of atmospheric aerosol optical properties focusing for the first time on Northeast Brazil (NEB) was performed based on four different remote sensing datasets: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Aerosol Robotic Network (AERONET), the Cloud-Aerosol LIDAR with Orthogonal Polarization (CALIOP) and a ground-based Lidar from Natal. We evaluated and identified distinct aerosol types, considering Aerosol Optical Depth (AOD) and Angström Exponent (AE). All analyses show that over the NEB, a low aerosol scenario prevails, while there are two distinct seasons of more elevated AOD that occur every year, from August to October and January to March. According to MODIS, AOD values ranges from 0.04 to 0.52 over the region with a mean of 0.20 and occasionally isolated outliers of up to 1.21. Aerosol types were identified as sea spray, biomass burning, and dust aerosols mostly transported from tropical Africa. Three case studies on days with elevated AOD were performed. All cases identified the same aerosol types and modeled HYSPLIT backward trajectories confirmed their source-dependent origins. This analysis is motivated by the implementation of an atmospheric chemistry model with an advanced data assimilation system that will use the observational database over NEB with the model to overcome high uncertainties in the model results induced by still unvalidated emission inventories.

Lidar data assimilation method based on CRTM and WRF-Chem models and its application in PM2.5 forecasts in Beijing

A three-dimensional variational (3DVAR) lidar data assimilation method is developed based on the Community Radiative Transfer Model (CRTM) and Weather Research and Forecasting model coupled to Chemistry (WRF-Chem) model. A 3DVAR data assimilation (DA) system using lidar extinction coefficient observation data is established, and variables from the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) mechanism of the WRF-Chem model are employed. Hourly lidar extinction coefficient data from 12:00 to 18:00 UTC on March 13, 2018 at four stations in Beijing are assimilated into the initial field of the WRF-Chem model; subsequently, a 24 h PM_2.5 concentration forecast is made. Results indicate that assimilating lidar data can effectively improve the subsequent forecast. PM_2.5 forecasts without using lidar DA are remarkably underestimated, particularly during heavy haze periods; in contrast, forecasts of PM_2.5 concentrations with lidar DA are closer to observations, the model low bias is evidently reduced, and the vertical distribution of the PM_2.5 concentration in Beijing is distinctly improved from the surface to 1200 m. Of the five aerosol species, improvements of NO₃^- are the most significant. The correlation coefficient between PM_2.5 concentration forecasts with lidar DA and observations at 12 stations in Beijing is increased by 0.45, and the corresponding average RMSE is decreased by 25 μg·m^-3, which respectively compared to those without DA.

Impacts of atmospheric vertical structures on transboundary aerosol transport from China to South Korea

To forecast haze pollution episodes caused by high concentrations of long-range transported pollutants emitted in the areas upstream of South Korea, it is crucial to study and identify their behaviour. We analysed the three-dimensional air quality structure in Seoul using ground observation data and aerosol lidar measurements to identify vertical aerosol intrusion into the Korean Peninsula during the spring of 2016. The intrusions were particularly affected by the development of the atmospheric boundary layer (ABL) in the leeward regions. The nocturnal pollutant intrusion into the Korean peninsula via the Yellow Sea was examined using measured data. The pollutants first reached the area above the nocturnal boundary layer (548 ± 180 m) and approached ground level on the following day due to convective mixing depending on the convective ABL growth (1182 ± 540 m) in daytime. These intrusion mechanisms were mostly attributed to extremely high concentrations (i.e. >100 μg m⁻³) of fine particulate matter in the leeward regions, accounting for four of the total of six cases for which the warnings and alerts were issued in Seoul Metropolitan Area over a year-long period (2016). The horizontal and vertical pathways of the long-range transported pollutants and the atmospheric vertical structure were identified as key factors affecting the surface air quality concentration in the leeward regions.

Improvement of aerosol optical properties modeling over Eastern Asia with MODIS AOD assimilation in a global non-hydrostatic icosahedral aerosol transport model

A new global aerosol assimilation system adopting a more complex icosahedral grid configuration is developed. Sensitivity tests for the assimilation system are performed utilizing satellite retrieved aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the results over Eastern Asia are analyzed. The assimilated results are validated through independent Aerosol Robotic Network (AERONET) observations. Our results reveal that the ensemble and local patch sizes have little effect on the assimilation performance, whereas the ensemble perturbation method has the largest effect. Assimilation leads to significantly positive effect on the simulated AOD field, improving agreement with all of the 12 AERONET sites over the Eastern Asia based on both the correlation coefficient and the root mean square difference (assimilation efficiency). Meanwhile, better agreement of the Ångström Exponent (AE) field is achieved for 8 of the 12 sites due to the assimilation of AOD only.

Estimating surface visibility at Hong Kong from ground-based LIDAR, sun photometer and operational MODIS products

Hong Kong's surface visibility has decreased in recent years due to air pollution from rapid social and economic development in the region. In addition to deteriorating health standards, reduced visibility disrupts routine civil and public operations, most notably transportation and aviation. Regional estimates of visibility solved operationally using available ground and satellite-based estimates of aerosol optical properties and vertical distribution may prove more effective than standard reliance on a few existing surface visibility monitoring stations. Previous studies have demonstrated that such satellite measurements correlate well with near-surface optical properties, despite these sensors do not consider range-resolved information and indirect parameterizations necessary to solve relevant parameters. By expanding such analysis to include vertically resolved aerosol profile information from an autonomous ground-based lidar instrument, this work develops six models for automated assessment of surface visibility. Regional visibility is estimated using co-incident ground-based lidar, sun photometer visibility meter and MODerate-resolution maging Spectroradiometer (MODIS) aerosol optical depth data sets. Using a 355 nm extinction coefficient profile solved from the lidar MODIS AOD (aerosol optical depth) is scaled down to the surface to generate a regional composite depiction of surface visibility. These results demonstrate the potential for applying passive satellite depictions of broad-scale aerosol optical properties together with a ground-based surface lidar and zenith-viewing sun photometer for improving quantitative assessments of visibility in a city such as Hong Kong.