A review on vulnerable atmospheric aerosol nanoparticles: Sources, impact on the health, ecosystem and management strategies

SKR Namasivayam, S Priyanka, M Lavanya… - Journal of …, 2024 - Elsevier
The Earth's atmosphere contains ultrafine particles known as aerosols, which can be either
liquid or solid particles suspended in gas. These aerosols originate from both natural …

Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts

M Gonçalves Ageitos, V Obiso, RL Miller… - Atmospheric …, 2023 - acp.copernicus.org
Soil dust aerosols are a key component of the climate system, as they interact with short-and
long-wave radiation, alter cloud formation processes, affect atmospheric chemistry and play …

Mineral dust cycle in the Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH) version 2.0

M Klose, O Jorba, M Gonçalves Ageitos… - Geoscientific Model …, 2021 - gmd.copernicus.org
We present the dust module in the Multiscale Online Non-hydrostatic AtmospheRe
CHemistry model (MONARCH) Version 2.0, a chemical weather prediction system that can …

Inverse modeling of the 2021 spring super dust storms in East Asia

J Jin, M Pang, A Segers, W Han, L Fang… - Atmospheric …, 2022 - acp.copernicus.org
This spring, super dust storms reappeared in East Asia after being absent for a (two) decade
(s). The event caused enormous losses both in Mongolia and in China. Accurate simulation …

Observing mineral dust in northern Africa, the Middle East, and Europe: current capabilities and challenges ahead for the development of dust Services

L Mona, V Amiridis, E Cuevas, A Gkikas… - Bulletin of the …, 2023 - journals.ametsoc.org
Mineral dust produced by wind erosion of arid and semiarid surfaces is a major component
of atmospheric aerosol that affects climate, weather, ecosystems, and socioeconomic …

[HTML][HTML] A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1. 0 and chemical transport model results from GEOS …

L Fang, J Jin, A Segers, H Liao, K Li… - Geoscientific Model …, 2023 - gmd.copernicus.org
Statistical methods, particularly machine learning models, have gained significant popularity
in air quality predictions. These prediction models are commonly trained using the historical …

Climatological assessment of the vertically resolved optical and microphysical aerosol properties by lidar measurements, sun photometer, and in situ observations …

S Lolli, M Sicard, F Amato, A Comeron… - Atmospheric …, 2023 - acp.copernicus.org
Aerosols are one of the most important pollutants in the atmosphere and have been
monitored for the past few decades by remote sensing and in situ observation platforms to …

Assimilating spaceborne lidar dust extinction improves dust forecasts

J Escribano, E Di Tomaso, O Jorba… - Atmospheric …, 2021 - acp.copernicus.org
Atmospheric mineral dust has a rich tri-dimensional spatial and temporal structure that is
poorly constrained in forecasts and analyses when only column-integrated aerosol optical …

[HTML][HTML] Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting

M Pang, J Jin, A Segers, H Jiang, W Han… - Geoscientific Model …, 2024 - gmd.copernicus.org
Dust storms pose significant risks to health and property, necessitating accurate forecasting
for preventive measures. Despite advancements, dust models grapple with uncertainties …

Evaluating the effects of columnar NO2 on the accuracy of aerosol optical properties retrievals

T Drosoglou, IP Raptis, M Valeri… - Atmospheric …, 2022 - amt.copernicus.org
We aim to evaluate the NO 2 absorption effect in aerosol properties derived from sun-sky
radiometers as well as the possible retrieval algorithm improvements by using more …