Dust Storms: An Overlooked Global Crisis Intensified by Climate Change
According to a UN report, sand and dust storms, worsened by climate change, are impacting health and environments globally, affecting over 330 million people. These storms significantly disrupt agriculture, transportation, and cause millions of premature deaths. The economic toll is considerable, particularly in the Middle East and North Africa.

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A United Nations World Meteorological Organisation (WMO) report has highlighted severe health and environmental impacts caused by sand and dust storms, exacerbated by climate change. Affecting over 330 million individuals in 150 countries, these storms represent a growing, yet often overlooked, global crisis, reports Al Jazeera.
Speaking on the issue, UNGA President Philemon Yang warned of the storms' broad impact, driven by deeper issues like climate change and unsustainable land practices. WMO Secretary-General Celeste Saulo pointed to the significant health risks, as well as disruptions in agriculture, transport, and renewable energy, reaffirming the storms' far-reaching consequences.
Yang revealed that airborne particles contribute to approximately seven million premature deaths yearly, linked to heart and respiratory illnesses. The storms are also detrimental to crop yields, poverty levels, and migration, affecting distant regions despite originating mainly from North Africa and the Middle East.
According to Laura Paterson, WMO's UN representative, two billion tonnes of dust—akin to 300 Great Pyramids of Giza—enter our atmosphere annually. UN Undersecretary-General, Rola Dashti, detailed the economic blow, estimating costs in the Middle East and North Africa at USD 150 billion annually, while the US recorded damages of USD 154 billion in 2017, a steep increase from 1995 figures.
The World Health Organisation has joined the WMO in issuing warnings of an escalating health crisis, noting that between 2018 and 2022, nearly 3.8 billion people were exposed to harmful dust levels, up significantly from previous data.
(With inputs from agencies.)