Improved Algorithms for Remote Sensing-Based Aerosol Retrieval during Extreme Biomass Burning Events

Characterization of Wildfire Smoke over Complex Terrain Using Satellite Observations, Ground-Based Observations, and Meteorological Models

The severity of wildfires is increasing globally. In this study, we used data from the Global Change Observation Mission-Climate/Second-generation Global Imager (GCOM-C/SGLI) to characterize the biomass burning aerosols that are generated by large-scale wildfires. We used data from the September 2020 wildfires in western North America. The target area had a complex topography, comprising a basin among high mountains along a coastal region. The SGLI was essential for dealing with the complex topographical changes in terrain that we encountered, as it contains 19 polarization channels ranging from near ultraviolet (380 nm and 412 nm) to thermal infrared (red at 674 nm and near-infrared at 869 nm) and has a fine spatial resolution (1 km). The SGLI also proved to be efficient in the radiative transfer simulations of severe wildfires through the mutual use of polarization and radiance. We used a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) to account for variations in meteorological conditions and/or topography. Ground-based aerosol measurements in the target area were sourced from the National Aeronautics and Space Administration-Aerosol Robotic Network; currently, official satellite products typically do not provide the aerosol properties for very optically thick cases of wildfires. This paper used satellite observations, ground-based observations, and a meteorological model to define an algorithm for retrieving the aerosol properties caused by severe wildfire events.

Estimation of Biogas Generated in Two Landfills in South-Central Ecuador

The landfill is a final disposal technique to confine municipal solid waste (MSW), where organic matter is degraded generating leachate and biogas composed of methane gases (CH4), carbon dioxide (CO2) and other gases that contribute to global warming. The objective of the current research was to estimate the amount of biogas generated through the LandGEM 3.03 mathematical model to determine the amount of electrical energy generated and the number of homes that would be supplied with electrical energy from 2021 to 2144. As a result of the application, it was estimated that in the Pichacay landfill, the highest point of biogas generation in 2053 would be 76,982,177 (m3/year) that would generate 81,226,339.36 (kWh/year), and would supply 5083 homes with electricity. Similarly, in the Las Iguanas landfill, the highest point would be 693,975,228 (m3/year) of biogas that produces 73,223,5296.7 (kWh/year) and would supply electricity to 45,825 homes. Of the performed gas analyses in the Pichacay landfill in 2020, an average of 51.49% CH4, 40.35% CO2, 1.75% O2 and 17.8% H2S was presented, while in the Las Iguanas landfill, for 2020 and 2021, we obtained an average of 51.88/CH4, 36.62% CO2, 1.01% O2 and 187.58 ppm H2S. Finally, the biogas generated by being harnessed minimizes the impacts related to global warming and climate change and would contribute electricity to the nearby communities.