A new study warns that even a minor scratch on a nonstick pan can release millions of microplastics and toxic “forever chemicals” into food.
Researchers in Australia found that damage to Teflon-coated cookware can cause an explosion of per- and polyfluorinated substances (PFAS), which have been linked to serious health risks, including cancer, infertility, and developmental disorders.
These chemicals, designed to resist heat and stains, are nearly impossible to break down and have been detected in 99% of Americans’ bloodstreams. With no strict federal regulations limiting PFAS exposure in cookware, experts advise avoiding nonstick pans altogether.
PFAS contamination is widespread, extending beyond kitchenware to clothing, bedding, and baby products. Scientists warn that these chemicals can linger in the body for years, increasing long-term health risks. Some states have begun banning PFAS in consumer products, but many Americans may find it difficult to completely avoid exposure.
Until safer alternatives become more accessible, researchers recommend using stainless steel or cast-iron cookware to minimize risks.
[Via: @toobaffled]
Abstract
The characterisation of microplastics is still difficult, and the challenge is even greater for nanoplastics. A possible source of these particles is the scratched surface of a non-stick cooking pot that is mainly coated with Teflon. Herein we employ Raman imaging to scan the surfaces of different non-stick pots and collect spectra as spectrum matrices, akin to a hyperspectral imaging process. We adjust and optimise different algorithms and create a new hybrid algorithm to extract the extremely weak signal of Teflon microplastics and particularly nanoplastics. We use multiple characteristic peaks of Teflon to create several images, and merge them to one, using a logic-based algorithm (i), in order to cross-check them and to increase the signal-noise ratio. To differentiate the varied peak heights towards image merging, an algebra-based algorithm (ii) is developed to process different images with weighting factors. To map the images via the whole set of the spectrum (not just from the individual characteristic peaks), a principal component analysis (PCA)-based algorithm (iii) is employed to orthogonally decode the spectrum matrix to the PCA spectrum and PCA intensity image. To effectively extract the Teflon spectrum information, a new hybrid algorithm is developed to justify the PCA spectra and merge the PCA intensity images with the algebra-based algorithm (PCA/algebra-based algorithm) (iv). Based on these developments and with the help of SEM, we estimate that thousands to millions of Teflon microplastics and nanoplastics might be released during a mimic cooking process. Overall, it is recommended that Raman imaging, along with the signal recognition algorithms, be combined with SEM to characterise and quantify microplastics and nanoplastics.