Studying the Impact on Urban Health over the Greater Delta Region in Egypt Due to Aerosol Variability Using Optical Characteristics from Satellite Observations and Ground-Based AERONET Measurements

This research addresses the aerosol characteristics and variability over Cairo and the Greater Delta region over the last 20 years using an integrative multi-sensor approach of remotely sensed and PM10 ground data. The accuracy of these satellite aerosol products is also evaluated and compared through cross-validation against ground observations from the AErosol RObotic NETwork (AERONET) project measured at local stations. The results show the validity of using Multi-angle Imaging Spectroradiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms for quantitative aerosol optical depth (AOD) assessment as compared to Ozone Monitoring Instrument (OMI), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), and POLarization and Directionality of the Earth’s Reflectances (POLDER). In addition, extracted MISR-based aerosol products have been proven to be quite effective in investigating the characteristics of mixed aerosols. Daily AERONET AOD observations were collected and classified using K-means unsupervised machine learning algorithms, showing five typical patterns of aerosols in the region under investigation. Four seasonal aerosol emerging episodes are identified and analyzed using multiple indicators, including aerosol optical depth (AOD), size distribution, single scattering albedo (SSA), and Ångström exponent (AE). The movements and detailed aerosol composition of the aforementioned episodes are demonstrated using NASA’s Goddard Space Flight Center (GSFC) back trajectories model in collaboration with aerosol subtype products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission. These episodes indicate that during the spring, fall, and summer, most of the severe aerosol events are caused by dust or mixed related scenarios, whereas during winter, aerosols of finer size lead to severe heavy conditions. It also demonstrates the impacts of different aerosol sources on urban human health, which are presented by the variations of multiple parameters, including solar radiation, air temperature, humidity, and UV exposure. Scarce ground PM10 data were collected and compared against satellite products, yet owed to their discrete nature of availability, our approach made use of the Random Decision Forest (RDF) model to convert satellite-based AOD and other meteorological parameters to predict PM10. The RDF model with inputs from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) and Global Land Data Assimilation System (GLDAS) datasets improves the performance of using AOD products to estimate PM10 values. The connection between climate variability and aerosol intensity, as well as their impact on health-related PM2.5 over Egypt is also demonstrated.

Evaluation of Parameterized Convective Transport of Trace Gases in Simulation of Storms Observed During the DC3 Field Campaign

Deep convective transport of surface moisture and pollution from the planetary boundary layer to the upper troposphere and lower stratosphere affects the radiation budget and climate. This study uses cloud-parameterized Weather Research and Forecasting model coupled with Chemistry simulations to analyze the subgrid deep convective transport of CO at 12- and 36-km horizontal resolution in supercell and mesoscale convective systems observed during the 2012 Deep Convective Clouds and Chemistry field campaign and compares the simulation results with aircraft measurements and cloud-resolved simulations. The best Weather Research and Forecasting simulation of these storms was obtained with the use of the Grell-Freitas convective scheme. The default Weather Research and Forecasting model coupled with Chemistry subgrid convective transport scheme was replaced with a scheme to compute convective transport within the Grell-Freitas subgrid cumulus parameterization, which resulted in improved transport simulations. We examined the CO tendencies due to subgrid- and grid-scale convective transport. Results showed that the subgrid convective transport started earlier than the grid-scale convective transport. The subgrid-scale convective transport reached its maximum during the hour prior to the formation of the grid-scale constant-altitude detrainment layer. After that, both the subgrid- and grid-scale convective transport began to decrease. The subgrid-scale convective transport played a more significant role in the supercell case than the mesoscale convective system case. Subgrid contribution reached ~90% at the beginning of the storm and decreased to ~30% (17%) for the 36-km (12-km) domain 4 hr later.