| Literature DB >> 30286589 |
Hyun-Joong Kang1, Hee-Jin Park1, Oh-Kyung Kwon2, Won-Seok Lee3, Dong-Hwan Jeong3, Byoung-Kyu Ju3, Jung-Hwan Kwon1,2.
Abstract
Municipal sewage treatment plants (STPs) are thought to be important point sources of microplastics in freshwater systems and many peer-reviewed articles have been published on this issue since mid-2010s. In this review, we summarize existing literature on the occurrence of microplastics in STPs and experimental methods used for isolation and identification of microplastics. The number concentrations of microplastics in STP influents were 15.1-640 L-1 , whereas those in the STP effluents were highly variable and ranged from not detectable to 65 L-1 . For most of cases, conventional STPs are removing microplastics very effectively. Fragments and fibers are dominant shapes of microplastics. Thermoplastics (polyethylene and polypropylene) and polyester are the predominant materials recovered. Although further research is needed, size distribution of microplastics in STPs is likely to follow a power law, implying that different studies using different size cutoffs may be compared after establishing a power law relationship.Entities:
Keywords: material type; microplastic identification; sewage treatment plants (STPs); shape; size distribution
Year: 2018 PMID: 30286589 PMCID: PMC6182249 DOI: 10.5620/eht.e2018013
Source DB: PubMed Journal: Environ Health Toxicol ISSN: 2233-6567
Summary of studies in which microplastics were identified in STP influents and effluents.
| Location | Information of STP | Sampling method | Analytical Method | Number concentration[ | Ref. | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Daily process capacity (×103 m3 d-1) | Population Equivalent (×1,000) | Sampling equipment | Sample volume (L) | Pretreatment | Analytical equipment | Size cut-off (mm) | Influent (MP L-1) | Effluent (MP L-1) | |||
| Influent | Effluent | ||||||||||
| Scotland | 261 | 650 | Steel buckets (10 L) | 30 | 50 | filter (11 μm) | dissection microscope & FT-IR | 11 | 15.7 ± 5.23 | 0.25 ± 0.04 | [ |
| Steel sieve (65 μm) | |||||||||||
| Sweden | 14 | Plankton net (mesh size; 300 μm) | 2 | 1,000 | stereo microscope & FT-IR | 300 | 15.1 ± 1.54 | 0.0082 ± 0.0017 | [ | ||
| Suction pump | |||||||||||
| USA | Steel sieve (400, 180, 45 μm) | 189,000-232,000 | microscope & FT-IR | 45 | 0 | [ | |||||
| Germany | 0.52-35 | 7-210 | Moble pumping device (10 μm stainless steel filter) | 390-1,000 | EM[ | micro FT-IR | 10 | 0-0.05[ | [ | ||
| WPO[ | 0.01-9[ | ||||||||||
| Netherland | Glass jar | 2 | 2 | filter (0.7 μm) | light microscopy & FT-IR | 0.7 | 73 ± 13 | 65 ± 67 | [ | ||
| USA | 189 | 680 | Steel sieve (5, 1, 0.355, 0.125 mm) | WPO | dissection microscope & micro FT-IR | 125 | [ | ||||
| Finland | 310-800 | Pump-filter device (200, 100, 20 μm) | 0.3 | 30-285 | stereo microscope | 20 | 610 | 13.5 ± 2.9 | [ | ||
| Finland | 270 | 800 | Pump-filter device (300, 100, 20 μm) | 0.1[ | 1,000[ | stereo microscope & FT-IR | 20 | 568[ | 2.5[ | [ | |
| 0.1[ | 10.5-13.5[ | 640[ | 0.6[ | ||||||||
| Australia | 13-308 | 67-1,227 | Stainless steel sieve (500, 190, 100, 25 μm) | 3-200 | WPO | dissection microscope & FT-IR | 25 | 0.21-1.5 | [ | ||
| USA | 2.3-382 | 3.5-56,000 | Tyler sieves (355, 125 μm) | 4,847 | WPO | dissection microscope | 125 | 0.05 ± 0.024 | [ | ||
| USA | 2.3-310 | Stainless steel sieve (355, 125 μm) | WPO | dissection microscope | 125 | 0.022-0.13 | [ | ||||
| Finland | 10 | Stainless steel bucket sieve (0.25, 5 mm) | 4-30 | WPO | optical microscope & FT-IR | 250 | 57.6 ± 32.8 | 1 ± 1.1 | [ | ||
| France | 240 | Automatic sampler | filter (1.6 μm) | stereomicroscope | 100 | 293 | 35 | [ | |||
| Finland | 14-88 | Pump-filter device (300, 100, 20 μm) | stereomicroscope & FT-IR | 20 | 0.04-1.2 | [ | |||||
| Canada | ISCO peristaltic pump 100 μm nylon mesh | 100 | WPO | stereomicroscope | 100 | 0.07 | [ | ||||
mean value±standard deviation;
enzymatic maceration;
wet peroxide oxidation;
MP size>500 mm;
MP size<500 mm;
grab sampling;
24-h composite sampling.
Figure 1.Relationship between the number concentration of microplastics in STP effluents and size cutoff. Mean values from literature are shown with error bars representing standard deviations.
Figure 2.Relative abundance in percent of material-types of microplastics identified in STP influents and effluents. Minimum, 25 percentile, median, 75 percentile, and maximum values from ref 27, 32, 34, 36, and 39 are presented in the box plot. (Abbreviations: PE=polyethylene, PP=polypropylene, PS=polystyrene, PET=polyethylene terephthalate, PA=polyacrylate, PU=polyurethane, PVC=polyvinyl chloride, PVA=polyvinyl alcohol, PPO=polyphenylene oxide, ABS=acrylonitrile butadiene styrene, SAN=styrene acrylonitrile, EVA=ethylene-vinyl acetate, PLA=polylactic acid, PLE=polyaryl ether).
Figure 3.Relative abundance in percent of shapes of microplastics identified in STP influents and effluents. Minimum, 25 percentile, median, 75 percentile, and maximum values from ref 28, 29, 31, 33, 34 are presented in the box plot.
Figure 4.Microplastic particle size distribution in (A) primary and secondary effluents from three wastewater treatment plants (WWTP) by Ziajahromi et al. [31] and in (B) influent and effluents after mechanical treatment, chemical and biological treatment, and final effluent by Talvitie et al. [37]. Dashed lines are best-fit using linear regression.