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Fig 1.

Sampling sites for sediment collection along the Loa River, Chile.

Figure adapted from OpenStreetMap.

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Fig 2.

Flowchart of the method for determining PET MPs in sediment samples.

The red arrows indicate the analytical purpose of each stage.

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Fig 3.

Results of staining of a) pre-digestion cellulose and b) post-digestion cellulose. Photographed at the excitation wavelength of 254 nm.

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Fig 4.

Results of the staining of the MPs used in this study, pre- digestion 254 nm a1) PET, b1) LDPE, c1) PP and d1) PS; post-digestion 254 nm a2) PET, b2) LDPE, c2) PP and d2) PS; post-digestion 365 nm a3) PET, b3) LDPE, c3) PP and d3) PS.

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Fig 5.

Results of the mass percentage recovery of microplastics at different temperatures of Microwave-assisted digestion, using HNO3/HCl mixture 3:1 v/v, for a time of 1 hour.

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Fig 6.

Melted LDPE microparticles, because of microwave-assisted acid digestion, for one hour at 120°C.

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Fig 7.

Removal of cellulose, in the digestion stage, at three different temperatures.

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Table 1.

Results of adding a pre-flotation step to the method using two saline’s solutions.

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Fig 8.

Spike and recovery of PET microplastics (MPs) was conducted under the following digestion conditions: Isolated PET microplastic particles (MPs PET), PET microplastics spiked into marine sediments (MPs PET with sediments), and a mixture of microplastic polymers (MPs Mix).

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Fig 9.

Spike and recovery results at different levels of MPs PET masses.

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Fig 10.

Identification of fluorescent emission colors for post-digestion microplastics standards of PET (a), PE (b), and PP (c) by using ChatGPT-4.0 artificial intelligence. The upper section provides the minimum and maximum RGB color range from IA color recognition for each plastic. To test the color range, images of fluorescent particles from each standard (1) were analyzed separately as samples using the same color range and each identified particle was marked in white (2).

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Fig 11.

Detection of PET, PE, and PP microplastic particles in a sediment sample from the Loa River using the RGB ranges proposed by the ChatGPT-4.0 artificial intelligence.

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Fig 12.

Determination of PET microplastic particles in sediment samples from the Loa River in Chile (n = 3).

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