Open AccessImproving the understanding between climate variability and observed extremes of global NO2 over the past 15 years
Author(s) -
Weizhi Deng,
Jason Blake Cohen,
Shuo Wang,
Chuyong Lin
Publication year - 2021
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/abd502
Subject(s) - climatology , radiative forcing , environmental science , north atlantic oscillation , arctic oscillation , empirical orthogonal functions , indian ocean dipole , forcing (mathematics) , arctic , climate model , climate change , atmospheric sciences , geography , aerosol , el niño southern oscillation , meteorology , oceanography , northern hemisphere , geology
This work addresses the relationship between major dynamical forcings and variability in NO 2 column measurements. The dominating impact in Northern Southeast Asia is due to El Niño-Southern Oscillation (ENSO); in Indonesia, Northern Australia and South America is due to Indian Ocean Dipole (IOD); and in Southern China Land and Sea, Populated Northern China, Siberia, Northern and Arctic Eurasia, Central and Southern Africa, and Western US and Canada is due to North Atlantic Oscillation (NAO). That NO 2 pollution in Indonesia is modulated by IOD contradicts previous work claiming that the emissions in Indonesia are a function of El Niño impacting upon Aerosol Optical Depth and Fire Radiative Power. Simultaneous impacts of concurrent and lagged forcings are derived using multi-linear regression, demonstrating ENSO impacts future NO 2 variability, enhancing NO 2 emissions 7–88 weeks in the future, while IOD and NAO in some cases increase the emissions from or the duration of the future burning season as measured by NO 2 . This impact will also extend to co-emitted aerosols and heat, which may impact the climate. In all cases, lagged forcings exhibit more impact than concurrent forcings, hinting at non-linearity coupling with soil moisture, water table, and other dynamical effects. The regression model formed demonstrates that dynamical forcings are responsible for over 45% of the NO 2 emissions variability in most non-urban areas and over 30% in urban China and sub-arctic regions. These results demonstrate the significance of climate forcing on short-lived air pollutants.