![]() ![]() Liqiang Zhang from Beijing Normal University, China, and colleagues explored how the sudden, dramatic reduction in particulate pollution in the region affected snow and ice melt, using multiple satellite data as well as a coupled atmosphere-chemistry-snow model. ![]() Diminished anthropogenic pollutant emissions during the 2020 Covid-19 lockdowns reduced snowmelt in the Himalayas, the study published in Proceedings of the National Academy of Sciences (PNAS) Nexus said. ![]() While much of this melting is attributable to climate change, air pollution also plays a role, because dark particles of dust and soot that fall on frozen surfaces absorb solar energy and melt the nearby snow and ice.Ī new study has revealed that as many as 27 metric tonnes of ice and snow melt in the Himalayas had been prevented by the Indian national lockdown, in place from March 25, 2020, to May 31, 2020. But with lower levels of snowfall, the sowing season has gone awry. Snowmelt and rainfall in the months of March and April would irrigate their fields enough to sow barley, wheat, peas, and potatoes. Scientists have recorded a retreat in both snowfall and glacial mass in Ladakh over the last few decades. However, ice and snow in the Himalayas have been melting at an accelerating rate in recent decades. Snow and ice on the Tibetan plateau act as a water source for over 20 per cent of the global population. These glaciers, which are the source of 10 major river systems, are warming much faster than the global average. The Hindu Kush Himalayan Region is also called the third pole because of the volume of glacial ice it stores. The five-week-long lockdown that India imposed in the year 2020 resulting in prevention of as many as 27 metric tonnes of ice and snow melt in the Himalayas, it has come to fore. Who would have thought that besides stopping the spread of the deadly Covid-19 Coronavirus, the lockdown imposed by the government also helped the world in general and India in particular in the ongoing fight to combat the climate change. ![]()
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