A new assessment advocates a global network of air monitoring stations to improve understandings of atmospheric particle distribution.
First published in the journal Current Pollution Reports, the study has identified huge knowledge gaps linked to airborne plastic pollution. Inconsistent measurement techniques, limited data, basic simulations, and poor understanding of atmospheric cycling mechanisms have all contributed to widespread grey areas.
The size of the problem — and how much plastic is being put out into the atmosphere — is one of the biggest uncertainties. Without this, it’s impossible to begin gauging the extent of the problem in health and environmental risk terms. Current estimates vary between 800 tonnes and 9million tonnes annually.
‘The scale of uncertainty around how much plastic is entering our atmosphere is alarming,’ said Zhonghua Zheng, Co-Lead for Environmental Data Science & AI at Manchester Environmental Research Institute (MERI) and Lecturer in Data Science & Environmental Analytics at The University of Manchester, credited as lead author of the paper.
‘Plastic pollution can have serious consequences for human health and ecosystems, so in order to assess the risks, we need to better understand how these particles behave in the atmosphere,’ they continued. ‘If we want to protect people and the planet, we need better data, better models, and global coordination.’
Three key recommendations have now been made which scientists believe could make it easier to asses how much of the 400million tonnes of plastic produced each year are finding a way into our atmosphere. A process that requires waste pieces to break down into micro (5mm or under) and nano (1micron or less) particles – small enough to enter the respiratory system, bloodstream, and bodily organs.
The team are now calling for:
*Expanding and standardising global observation networks
*Improving and refining atmospheric modelling
*Harnessing the power of artificial intelligence [AI]
‘By adopting this integrated approach, we can fundamentally transform how we understand and manage this emerging threat,’ said Fei Jiang, PhD researcher at The University of Manchester. ‘AI can play a powerful role in analysing data and simulating plastic movement, it can help make sense of fragmented datasets, detect hidden patterns, and integrate information from multiple sources – but it needs good quality data to work with. All of these areas must work hand in hand to manage this emerging threat and shape effective global pollution strategies.’
Image: Nick Russill / Unsplash
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