Triple dip La-Nina, unorthodox circulation and unusual spin in air quality of India.

The recent La-Nina phase of the El Nino Southern Oscillation (ENSO) phenomenon unusually lasted for third consecutive year, has disturbed global weather and linked to Indian monsoon. However, our understanding on the linkages of such changes to regional air quality is poor. We hereby provide a mechanism that beyond just influencing the meteorology, the interactions between the ocean and the atmosphere during the retreating phase of the La-Niña produced secondary results that significantly influenced the normal distribution of air quality over India through disturbed large-scale wind patterns. The winter of 2022-23 that coincided with retreating phase of the unprecedented triple dip La-Niña, was marred by a mysterious trend in air quality in different climatological regions of India, not observed in recent decades. The unusually worst air quality over South-Western India, whereas relatively cleaner air over the highly polluted North India, where levels of most toxic pollutant (PM2.5) deviating up to about ±30 % from earlier years. The dominance of higher northerly wind in the transport level forces influx and relatively slower winds near the surface, trapping pollutants in peninsular India, thereby notably increasing PM2.5 concentration. In contrast, too feeble western disturbances, and unique wind patterns with the absence of rain and clouds and faster ventilation led to a significant improvement in air quality in the North. The observed findings are validated by the chemical-transport model when forced with the climatology of the previous year. The novelty of present research is that it provides an association of air quality with climate change. We demonstrate that the modulated large-scale wind patterns linked to climatic changes may have far-reaching consequences even at a local scale leading to unusual changes in the distribution of air pollutants, suggesting ever-stringent emission control actions.

Process-based diagnostics of extreme pollution trail using numerical modelling during fatal second COVID-19 wave in the Indian capital.

The world's worst outbreak, the second COVID-19 wave, not only unleashed unprecedented devastation of human life, but also made an impact of lockdown in the Indian capital, New Delhi, in particulate matter (PM: PM2.5 and PM10) virtually ineffective during April to May 2021. The air quality remained not only unabated but also was marred by some unusual extreme pollution events. SAFAR-framework model simulations with different sensitivity experiments were conducted using the newly developed lockdown emission inventory to understand various processes responsible for these anomalies in PM. Model results well captured the magnitude and variations of the observed PM before and after the lockdown but significantly underestimated their levels in the initial period of lockdown followed by the first high pollution event when the mortality counts were at their peak (∼400 deaths/day). It is believed that an unaccounted emission source was playing a leading role after balancing off the impact of curtailed lockdown emissions. The model suggests that the unprecedented surge in PM10 (690 µg/m3) on May 23, 2021, though Delhi was still under lockdown, was associated with large-scale dust transport originating from the north west part of India combined with the thunderstorm. The rainfall and local dust lifting played decisive roles in other unusual events. Obtained results and the proposed interpretation are likely to enhance our understanding and envisaged to help policymakers to frame suitable strategies in such kinds of emergencies in the future.

Association of retreating monsoon and extreme air pollution in a megacity.

The world's top ranked mega city Delhi is known for deteriorated air quality. However, the analysis of air pollution data of 5 years (2014-2018) reveals that years 2016 and 2017, which were marked by an unusual delayed withdrawal of monsoon, witnessed an unprecedented extreme levels of toxic PM2.5 particles (≤2.5 µm in diameter) touching a peak level of ∼760 µg/m3 (24 hr average), immediately after the monsoon retreat, surpassing WHO standards by ∼30 time and Indian national standards by ∼12 times, jeopardising lives of its citizens. However, the normal monsoon withdrawal years do not show such extreme levels of pollution. The high resolution WRF-Chem model along with meteorological data are used in this work to understand that how the delayed monsoon withdrawal and associated vagarious anti-cyclonic circulation resulted in trapping externally generated pollutants ceaselessly under colder conditions, leading to historic air quality crisis in landlocked mega city in these selected years. The sensitivity analysis confirmed that when WRF-chem model forced the climatology of normal monsoon year (2015) to simulate the pollution scenario of 2016 and 2017 for the above time period, the crisis subsided. Present findings suggest that such unusual monsoon patterns are on the hook to spur extreme pollution events in recent time.