A novel way to rapidly monitor microplastics in soil by hyperspectral imaging technology and chemometrics
- 1. School of Food and Environment, Dalian Univeristy of Technology, 2 Dagong Road, Liaodongwan New District, Panjin City, Liaoning Province, 124221 (China)
- 2. State Key Laboratory of Environmental Criteria & Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012 (China)
Description
Highlights: • Hyperspectral technology was investigated to detect microplastic in soil rapidly. • Two color PE microplastics with particle size from 0.5 to 1 mm were studied. • Support vector machine showed the potential to monitor PE microplastics in soil. • Six kinds of household polymers were applied to validate the developed method. Hyperspectral imaging technology has been investigated as a possible way to detect microplastics contamination in soil directly and efficiently in this study. Hyperspectral images with wavelength range between 400 and 1000 nm were obtained from soil samples containing different materials including microplastics, fresh leaves, wilted leaves, rocks and dry branches. Supervised classification algorithms such as support vector machine (SVM), mahalanobis distance (MD) and maximum likelihood (ML) algorithms were used to identify microplastics from the other materials in hyperspectral images. To investigate the effect of particle size and color, white polyethylene (PE) and black PE particles extracted from soil with two different particle size ranges (1–5 mm and 0.5–1 mm) were studied in this work. The results showed that SVM was the most applicable method for detecting white PE in soil, with the precision of 84% and 77% for PE particles in size ranges of 1–5 mm and 0.5–1 mm respectively. The precision of black PE detection achieved by SVM were 58% and 76% for particles of 1–5 mm and 0.5–1 mm respectively. Six kinds of household polymers including drink bottle, bottle cap, rubber, packing bag, clothes hanger and plastic clip were used to validate the developed method, and the classification precision of polymers were obtained from 79% to 100% and 86%–99% for microplastics particle 1–5 mm and 0.5–1 mm respectively. The results indicate that hyperspectral imaging technology is a potential technique to determine and visualize the microplastics with particle size from 0.5 to 5 mm on soil surface directly.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.envpol.2018.03.026Additional details
Identifiers
- DOI
- 10.1016/j.envpol.2018.03.026;
- PII
- S0269749117349254;
Publishing Information
- Journal Title
- Environmental Pollution (1987)
- Journal Volume
- 238
- Journal Page Range
- p. 121-129
- ISSN
- 0269-7491
- CODEN
- ENPOEK
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 53005934
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- ALGORITHMS; CONTAMINATION; MAXIMUM-LIKELIHOOD FIT; MONITORING; PARTICLE SIZE; PLASTICS; POLYETHYLENES; ROCKS; RUBBERS; SOILS; SPECTROSCOPY
- Descriptors DEC
- ELASTOMERS; MATERIALS; MATHEMATICAL LOGIC; MATHEMATICAL SOLUTIONS; NUMERICAL SOLUTION; ORGANIC COMPOUNDS; ORGANIC POLYMERS; PETROCHEMICALS; PETROLEUM PRODUCTS; POLYMERS; POLYOLEFINS; SIZE; SYNTHETIC MATERIALS
Optional Information
- Copyright
- Copyright (c) 2018 Elsevier Ltd. All rights reserved.