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Direct radiative effects of airborne microplastics

Nature volume 598, pages 462–467 (2021)Cite this article

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Abstract

Microplastics are now recognized as widespread contaminants in the atmosphere, where, due to their small size and low density, they can be transported with winds around the Earth1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25. Atmospheric aerosols, such as mineral dust and other types of airborne particulate matter, influence Earth’s climate by absorbing and scattering radiation (direct radiative effects) and their impacts are commonly quantified with the effective radiative forcing (ERF) metric26. However, the radiative effects of airborne microplastics and associated implications for global climate are unknown. Here we present calculations of the optical properties and direct radiative effects of airborne microplastics (excluding aerosol–cloud interactions). The ERF of airborne microplastics is computed to be 0.044 ± 0.399 milliwatts per square metre in the present-day atmosphere assuming a uniform surface concentration of 1 microplastic particle per cubic metre and a vertical distribution up to 10 kilometres altitude. However, there are large uncertainties in the geographical and vertical distribution of microplastics. Assuming that they are confined to the boundary layer, shortwave effects dominate and the microplastic ERF is approximately −0.746 ± 0.553 milliwatts per square metre. Compared with the total ERF due to aerosol–radiation interactions27 (−0.71 to −0.14 watts per square metre), the microplastic ERF is small. However, plastic production has increased rapidly over the past 70 years28; without serious attempts to overhaul plastic production and waste-management practices, the abundance and ERF of airborne microplastics will continue to increase.

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Fig. 1: Concentrations of airborne microplastics reported by previous studies.
Fig. 2: Optical properties of microplastic fragments and fibres.
Fig. 3: ERF of airborne microplastics.

Data availability

GCM data that support the findings of this study are available at https://doi.org/10.5281/zenodo.5093843. Source data are provided with this paper.

Code availability

Custom code generated in this study is available at https://doi.org/10.5281/zenodo.5093843.

References

  1. Akhbarizadeh, R. et al. Suspended fine particulate matter (PM2.5), microplastics (MPs), and polycyclic aromatic hydrocarbons (PAHs) in air: Their possible relationships and health implications. Environ. Res. 192, 110339 (2021).

    Article  CAS  PubMed  Google Scholar 

  2. Allen, S. et al. Atmospheric transport and deposition of microplastics in a remote mountain catchment. Nat. Geosci. 12, 339–344 (2019).

    Article  CAS  ADS  Google Scholar 

  3. Allen, S. et al. Examination of the ocean as a source for atmospheric microplastics. PLoS ONE 15, e0232746 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Bergmann, M. et al. White and wonderful? Microplastics prevail in snow from the Alps to the Arctic. Sci. Adv. 5, eaax1157 (2019).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  5. Brahney, J., Hallerud, M., Heim, E., Hahnenberger, M. & Sukumaran, S. Plastic rain in protected areas of the United States. Science 368, 1257–1260 (2020).

    Article  CAS  PubMed  ADS  Google Scholar 

  6. Cai, L. et al. Characteristic of microplastics in the atmospheric fallout from Dongguan city, China: preliminary research and first evidence. Environ. Sci. Pollut. Res. Int. 24, 24928–24935 (2017).

    Article  PubMed  Google Scholar 

  7. Dris, R., Gasperi, J., Saad, M., Mirande, C. & Tassin, B. Synthetic fibers in atmospheric fallout: a source of microplastics in the environment? Mar. Pollut. Bull. 104, 290–293 (2016).

    Article  CAS  PubMed  Google Scholar 

  8. Dris, R. et al. A first overview of textile fibers, including microplastics, in indoor and outdoor environments. Environ. Pollut. 221, 453–458 (2017).

    Article  CAS  PubMed  Google Scholar 

  9. Gaston, E., Woo, M., Steele, C., Sukumaran, S. & Anderson, S. Microplastics differ between indoor and outdoor air masses: insights from multiple microscopy methodologies. Appl. Spectrosc. 74, 1079–1098 (2020).

    Article  CAS  PubMed  ADS  Google Scholar 

  10. Klein, M. & Fischer, E. K. Microplastic abundance in atmospheric deposition within the metropolitan area of Hamburg, Germany. Sci. Total Environ. 685, 96–103 (2019).

    Article  CAS  PubMed  ADS  Google Scholar 

  11. Knobloch, E. et al. Comparison of deposition sampling methods to collect airborne microplastics in Christchurch, New Zealand. Wat. Air Soil Pollut. 232, 133 (2021).

    Article  CAS  ADS  Google Scholar 

  12. Levermore, J. M., Smith, T. E. L., Kelly, F. J. & Wright, S. L. Detection of microplastics in ambient particulate matter using Raman spectral imaging and chemometric analysis. Anal. Chem. 92, 8732–8740 (2020).

    Article  CAS  PubMed  Google Scholar 

  13. Li, Y. et al. Airborne fiber particles: types, size and concentration observed in Beijing. Sci. Total Environ. 705, 135967 (2020).

    Article  CAS  PubMed  ADS  Google Scholar 

  14. Liu, K. et al. Source and potential risk assessment of suspended atmospheric microplastics in Shanghai. Sci. Total Environ. 675, 462–471 (2019).

    Article  CAS  PubMed  ADS  Google Scholar 

  15. Liu, K. et al. Consistent transport of terrestrial microplastics to the ocean through atmosphere. Environ. Sci. Technol. 53, 10612–10619 (2019).

    Article  CAS  PubMed  ADS  Google Scholar 

  16. Liu, C. et al. Widespread distribution of PET and PC microplastics in dust in urban China and their estimated human exposure. Environ. Int. 128, 116–124 (2019).

    Article  CAS  PubMed  Google Scholar 

  17. Liu, K. et al. Global inventory of atmospheric fibrous microplastics input into the ocean: an implication from the indoor origin. J. Hazard. Mater. 400, 123223 (2020).

    Article  PubMed  Google Scholar 

  18. Materić, D. et al. Micro- and nanoplastics in Alpine snow: a new method for chemical identification and (semi)quantification in the nanogram range. Environ. Sci. Technol. 54, 2353–2359 (2020).

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  19. Su, L., Nan, B., Craig, N. J. & Pettigrove, V. Temporal and spatial variations of microplastics in roadside dust from rural and urban Victoria, Australia: implications for diffuse pollution. Chemosphere 252, 126567 (2020).

    Article  CAS  PubMed  ADS  Google Scholar 

  20. Syafei, A. D., Nurasrin, N. R., Assomadi, A. F. & Boedisantoso, R. Microplastic pollution in the ambient air of Surabaya, Indonesia. Curr. World Environ. 61, 290–298 (2019).

  21. Wang, X. et al. Atmospheric microplastic over the South China Sea and East Indian Ocean: abundance, distribution and source. J. Hazard. Mater. 389, 121846 (2020).

    Article  CAS  PubMed  Google Scholar 

  22. Wright, S. L., Ulke, J., Font, A., Chan, K. L. A. & Kelly, F. J. Atmospheric microplastic deposition in an urban environment and an evaluation of transport. Environ. Int. 136, 105411 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zhang, Y. et al. Microplastics in glaciers of the Tibetan Plateau: evidence for the long-range transport of microplastics. Sci. Total Environ. 758, 143634 (2021).

    Article  CAS  PubMed  ADS  Google Scholar 

  24. Brahney, J. et al. Constraining the atmospheric limb of the plastic cycle. Proc. Natl Acad. Sci. USA 118, e2020719118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Evangeliou, N. et al. Atmospheric transport is a major pathway of microplastics to remote regions. Nat. Commun. 11, 3381 (2020).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  26. Myhre, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) Ch. 8 (IPCC, Cambridge Univ. Press, 2013).

  27. Bellouin, N. et al. Bounding global aerosol radiative forcing of climate change. Rev. Geophys. 58, e2019RG000660 (2020).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  28. Geyer, R., Jambeck, J. R. & Law, K. L. Production, use, and fate of all plastics ever made. Sci. Adv. 3, e1700782 (2017).

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  29. Andrady, A. L. Microplastics in the marine environment. Mar. Pollut. Bull. 62, 1596–1605 (2011).

    Article  CAS  PubMed  Google Scholar 

  30. de Souza Machado, A. A., Kloas, W., Zarfl, C., Hempel, S. & Rillig, M. C. Microplastics as an emerging threat to terrestrial ecosystems. Glob. Change Biol. 24, 1405–1416 (2018).

    Article  ADS  Google Scholar 

  31. Rochman, C. M. Microplastics research—from sink to source. Science 360, 28–29 (2018).

    Article  CAS  PubMed  ADS  Google Scholar 

  32. Goodman, K. E., Hare, J. T., Khamis, Z. I., Hua, T. & Sang, Q.-X. A. Exposure of human lung cells to polystyrene microplastics significantly retards cell proliferation and triggers morphological changes. Chem. Res. Toxicol. 34, 1069–1081 (2021).

  33. Spracklen, D. V. et al. Explaining global surface aerosol number concentrations in terms of primary emissions and particle formation. Atmos. Chem. Phys. 10, 4775–4793 (2010).

    Article  CAS  ADS  Google Scholar 

  34. Bullard, J. E., Ockelford, A., O’Brien, P. & McKenna Neuman, C. Preferential transport of microplastics by wind. Atmos. Environ. 245, 118038 (2021).

    Article  CAS  Google Scholar 

  35. Tsigaridis, K. & Kanakidou, M. The Present and future of secondary organic aerosol direct forcing on climate. Curr. Clim. Change Rep. 4, 84–98 (2018).

    Article  Google Scholar 

  36. González-Pleiter, M. et al. Occurrence and transport of microplastics sampled within and above the planetary boundary layer. Sci. Total Environ. 761, 143213 (2020).

  37. Mishra, A. K., Koren, I. & Rudich, Y. Effect of aerosol vertical distribution on aerosol-radiation interaction: a theoretical prospect. Heliyon 1, e00036 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Lohmann, U. et al. Total aerosol effect: radiative forcing or radiative flux perturbation? Atmos. Chem. Phys. 10, 3235–3246 (2010).

    Article  CAS  ADS  Google Scholar 

  39. Bellouin, N. et al. Aerosol forcing in the Climate Model Intercomparison Project (CMIP5) simulations by HadGEM2-ES and the role of ammonium nitrate. J. Geophys. Res. 116, D20206 (2011).

  40. Jervis, D. A. Optical brighteners: improving the colour of plastics. Plast. Addit. Compd 5, 42–46 (2003).

  41. Twomey, S. The influence of pollution on the shortwave albedo of clouds. J. Atmos. Sci. 34, 1149–1152 (1977).

    Article  ADS  Google Scholar 

  42. Albrecht, B. A. Aerosols, cloud microphysics, and fractional cloudiness. Science 245, 1227–1230 (1989).

    Article  CAS  PubMed  ADS  Google Scholar 

  43. Ganguly, M. & Ariya, P. A. Ice Nucleation of model nanoplastics and microplastics: a novel synthetic protocol and the influence of particle capping at diverse atmospheric environments. ACS Earth Space Chem. 3, 1729–1739 (2019).

    Article  CAS  Google Scholar 

  44. Vergara-Temprado, J. et al. Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles. Proc. Natl Acad. Sci. USA 115, 2687–2692 (2018).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  45. Eriksen, M. et al. Plastic pollution in the world’s oceans: more than 5 trillion plastic pieces weighing over 250,000 tons afloat at sea. PLoS ONE 9, e111913 (2014).

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  46. Boé, J., Somot, S., Corre, L. & Nabat, P. Large discrepancies in summer climate change over Europe as projected by global and regional climate models: causes and consequences. Clim. Dyn. 54, 2981–3002 (2020).

    Article  Google Scholar 

  47. Wessel, P. & Smith, W. H. F. A global self-consistent, hierarchical, high-resolution shoreline database. J. Geophys. Res. Solid Earth 101, 8741–8743 (1996).

    Article  Google Scholar 

  48. Python Language Reference, Version 3.6 https://www.python.org/downloads/release/python-360/ (Python Software Foundation).

  49. Horwitz, J. W. Infrared refractive index of polyethylene and a polyethylene-based material. Opt. Eng. 50, 093603 (2011).

    Article  ADS  CAS  Google Scholar 

  50. Smith, D. R. & Loewenstein, E. V. Optical constants of far infrared materials. 3: plastics. Appl. Opt. 14, 1335–1341 (1975).

    Article  CAS  PubMed  ADS  Google Scholar 

  51. Sultanova, N., Kasarova, S. & Nikolov, I. Dispersion Properties of Optical Polymers. Acta Phys. Pol. A 116, 585–587 (2009).

    Article  CAS  ADS  Google Scholar 

  52. Zhang, X., Qiu, J., Zhao, J., Li, X. & Liu, L. Complex refractive indices measurements of polymers in infrared bands. J. Quant. Spectrosc. Radiat. Transf. 252, 107063 (2020).

    Article  CAS  Google Scholar 

  53. Zhang, X., Qiu, J., Li, X., Zhao, J. & Liu, L. Complex refractive indices measurements of polymers in visible and near-infrared bands. Appl. Opt. 59, 2337–2344 (2020).

    Article  CAS  PubMed  ADS  Google Scholar 

  54. Flores-Mijangos, J. & Beltrán-López, V. Far-infrared laser measurement of the refractive index of polypropylene. Appl. Opt. 42, 592–596 (2003).

    Article  CAS  PubMed  ADS  Google Scholar 

  55. Myers, T. L. et al. Accurate measurement of the optical constants n and k for a series of 57 inorganic and organic liquids for optical modeling and detection. Appl. Spectrosc. 72, 535–550 (2018).

    Article  CAS  PubMed  ADS  Google Scholar 

  56. Sellmeier, W. Ueber die durch die Aetherschwingungen erregten Mitschwingungen der Körpertheilchen und deren Rückwirkung auf die ersteren, besonders zur Erklärung der Dispersion und ihrer Anomalien. Ann. Phys. 223, 386–403 (1872).

    Article  Google Scholar 

  57. Kroon, F. J., Motti, C. E., Jensen, L. H. & Berry, K. L. E. Classification of marine microdebris: a review and case study on fish from the Great Barrier Reef, Australia. Sci. Rep. 8, 16422 (2018).

    Article  PubMed  PubMed Central  ADS  CAS  Google Scholar 

  58. Plastics—The Facts 2018: An Analysis of European Plastics Production, Demand and Waste Data (PlasticsEurope, 2018); http://www.plasticseurope.org

  59. China Leads in Growth of Polymers & Plastic Products, (Plastemart, 2006); www.plastemart.com/upload/Literature/chineseplasticandpolymergrowth.asp

  60. Edwards, J. M. & Slingo, A. Studies with a flexible new radiation code. I: choosing a configuration for a large-scale model. Q. J. R. Meteorol. Soc. 122, 689–719 (1996).

    Article  ADS  Google Scholar 

  61. Lean, J. L. & DeLand, M. T. How does the Sun’s spectrum vary? J. Clim. 25, 2555–2560 (2012).

    Article  ADS  Google Scholar 

  62. Kokhanovsky, A. A. & Zege, E. P. Local optical parameters of spherical polydispersions: simple approximations. Appl. Opt. 34, 5513–5519 (1995).

    Article  CAS  PubMed  ADS  Google Scholar 

  63. van de Hulst, H. C. Light Scattering by Small Particles (Wiley, 1957).

  64. Kokhanovsky, A. A. & Macke, A. Integral light-scattering and absorption characteristics of large, nonspherical particles. Appl. Opt. 36, 8785–8790 (1997).

    Article  CAS  PubMed  ADS  Google Scholar 

  65. Bohren, C. F. & Huffman, D. R. Absorption and Scattering of Light by Small Particles (John Wiley & Sons Inc., 1983).

  66. Duntley, S. Q. The optical properties of diffusing materials. J. Opt. Soc. Am. 32, 61–70 (1942).

    Article  ADS  Google Scholar 

  67. Walters, D. et al. The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations. Geosci. Model Dev. 12, 1909–1963 (2019).

    Article  CAS  ADS  Google Scholar 

  68. Edwards, J. M., Manners, J., Thelen, J.-C., Ingram, W. J. & Hill, P. G. Unified Model Documentation Paper 023: The Radiation Code (UM Version 11.4) (Met Office, 2018).

  69. Lamarque, J. F. et al. Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos. Chem. Phys. 10, 7017–7039 (2010).

    Article  CAS  ADS  Google Scholar 

  70. Forster, P. M. et al. Recommendations for diagnosing effective radiative forcing from climate models for CMIP6. J. Geophys. Res. Atmos. 121, 12460–12475, (2016).

    Article  ADS  Google Scholar 

  71. Oreopoulos, L. & Mlawer, E. Modeling: the Continual Intercomparison of Radiation Codes (CIRC). Bull. Am. Meteorol. Soc. 91, 305–310 (2010).

    Article  ADS  Google Scholar 

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Acknowledgements

This research was supported by the Royal Society of New Zealand Marsden Fund (contract number MFP-UOC1903). We acknowledge the UK Met Office for the use of the MetUM, SOCRATES and the Continual Intercomparison of Radiation Codes (CIRC). We acknowledge the contribution of New Zealand eScience Infrastructure (NeSI) high-performance computing facilities to the results of this research. New Zealand’s national facilities are provided by NeSI and funded jointly by NeSI’s collaborator institutions and through the Ministry of Business, Innovation and Employment’s Research Infrastructure programme (https://www.nesi.org.nz, last access: 20 April 2021). We also acknowledge the use of the Rāpoi computing facility at Victoria University of Wellington, along with the open source software used in the analysis: Devuan GNU+Linux, Python, numpy, scipy and matplotlib. L.E.R. thanks Jonny Williams for technical assistance. L.E.R. and P.K. acknowledge R. Martinez Gazoni for helpful discussions.

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Author notes

  1. Peter Kuma

    Present address: Department of Meteorology, Stockholm University, Stockholm, Sweden

Authors and Affiliations

  1. School of Physical and Chemical Sciences, University of Canterbury, Christchurch, New Zealand

    Laura E. Revell, Peter Kuma & Sally Gaw

  2. The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Chemical and Physical Sciences, Victoria University of Wellington, Wellington, New Zealand

    Eric C. Le Ru & Walter R. C. Somerville

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  1. Laura E. Revell
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Contributions

L.E.R. Conceptualized the study, acquired funding, supervised the study, wrote the original draft and conducted the analysis together with P.K. and W.R.C.S. . P.K. contributed to the methodology, software, validation, and writing of the original draft. E.C.L.R. contributed to the methodology, validation, funding acquisition, supervision and review and editing of the manuscript. W.R.C.S. contributed to the methodology and validation, and writing of  the original draft. S.G. reviewed and edited the manuscript and contributed to funding acquisition.

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Correspondence to Laura E. Revell.

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Extended data figures and tables

Extended Data Fig. 1 Composition of airborne microplastics collected in previous studies compared with reported plastic production data.

The studies included disaggregated composition by morphotype and are presented for (a) fragments; (b) fibres. Polymer compositions include acrylic (ACR, including polyacrylonitrile and poly(N-methyl acrylamide)), polyamide (PA, including nylon), polyethylene and polypropylene (PE-PP), polyester (PES, including polyethylene terephthalate), polystyrene (PS), polyurethane (PUR), polyvinyl acetate (PVA), polyvinyl chloride (PVC), resins (RES, including epoxy, phenoxy and alkyd resins), and various other types (OTH)

Source data.

Extended Data Fig. 2 Size distributions of microplastic fragments reported by previous studies.

A gamma distribution was fitted to match the majority of the empirical distributions. The distributions are normalized to unity and approximated by a gamma distribution with the shape parameter of 2 and scale parameter 15 μm

Source data.

Extended Data Fig. 3 Size distributions of microplastic fibre lengths reported by previous studies.

A gamma distribution was fitted to match the majority of the empirical distributions. The distributions are normalized to unity and approximated by a gamma distribution with the shape parameter of 2.5 and scale parameter 250 μm

Source data.

Extended Data Fig. 4

Morphotypes of airborne microplastic collected in previous studies

Source data.

Extended Data Fig. 5 Refractive index of polymers based on a literature survey.

Polymer compositions include high-density polyethylene (HDPE), polyacrylic acid (PAA), polyethylene terephthalate (PET), polypropylene (PP), polystyrene (PS) and polyvinyl chloride (PVC). The mean calculated over regular wavelength intervals on a log10 scale is shown by the dashed black lines. In (a) equation (2) was fitted to the mean. In (b) equation (3) was used to fit a 4th degree polynomial to the log10 of the mean using the least squares method. The solid black lines represent the fits given by equations (2) and 3, and these fits were used in the calculations of microplastic optical properties

Source data.

Extended Data Fig. 6 Colours of airborne microplastics collected in previous studies, where colour was reported.

Black includes grey; blue includes turquoise; green includes lime; red includes pink, purple, brown and orange; white includes transparent

Source data.

Extended Data Fig. 7 The empirical aspect ratio of fibres collected in European and Arctic snow (the only study to date to report fibre aspect ratio).

A least squares fit of the form \(D=A\,\log \left(1+\frac{L}{B}\right)\) is also shown, where D is the fibre diameter, L is the fibre length and A and B are fitted coefficients, rounded to the nearest integer

Source data.

Extended Data Table 1 Prescribed microplastic surface concentrations in GCM simulations 
Full size table
Extended Data Table 2 Optical properties of microplastic fragments and fibres supplied to the GCM in the shortwave and longwave bands
Full size table

Source data

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Revell, L.E., Kuma, P., Le Ru, E.C. et al. Direct radiative effects of airborne microplastics. Nature 598, 462–467 (2021). https://doi.org/10.1038/s41586-021-03864-x

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