1. Automated machine learning to evaluate the information content of tropospheric trace gas columns for fine particle estimates over India: a modeling testbed Zheng, Zhonghua; Fiore, Arlene M.; Westervelt, Daniel M.; Milly, George P.; Goldsmith, Jeff; Karambelas, Alexandra N.; Curci, Gabriele; Randles, Cynthia A.; Paiva, Antonio R.; Wang, Chi; Wu, Qingyun; Dey, Sagnik 2022 Data (Information) Atmospheric aerosolsAir--Pollution--Remote sensingAtmospheric chemistryTropospheric chemistryMachine learning
2. Crop residue burning practices across north India inferred from household survey data: Bridging gaps in satellite observations Liu, Tianjia; Mickley, Loretta J.; Singh, Sukhwinder; Jain, Meha; DeFries, Ruth S.; Marlier, Miriam E. 2020 Articles Prescribed burningPrescribed burning--Environmental aspectsAir qualityAir--Pollution--Remote sensingHousehold surveys
3. Predicting fine-scale daily NO₂ over Mexico city using an ensemble modeling approach He, Mike Zhongyu; Yitshak-Sade, Maayan; Just, Allan C.; Gutiérrez-Avila, Iván; Dorman, Michael; de Hoogh, Kees; Mijling, Bas; Wright, Robert O.; Kloog, Itai 2023 Articles Air--Pollution--MeasurementAir--Pollution--Remote sensingNitrogen dioxideEpidemiology
4. Space-based diagnosis of surface ozone sensitivity to anthropogenic emissions Martin, Randall V.; Fiore, Arlene M.; Van Donkelaar, Aaron 2004 Articles Climatic changes--Effect of human beings onOzone layerAtmospheric nitrogen oxidesAir--Pollution--Remote sensingClimatic changesAtmospheric chemistry