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A systematic light pollution modelling bias in present night sky brightness predictions

Nature Astronomy volume 7, pages 269–279 (2023)Cite this article

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Abstract

Night sky brightness (NSB) measurements inform both the selection of new ground-based optical and near-infrared astronomical observatory sites and the management of night-time conditions near existing facilities. NSB modelling supports site characterization in cases where obtaining in situ measurements is difficult and provides additional information about the photic environment. Models of NSB conventionally assume Mie scattering, but we show that predominantly at low-altitude sites contaminated by artificial light, this assumption may result in significant errors up to a factor of ~2.5. This effect introduces systematic bias to models of anthropogenic skyglow, but more realistic modelling approaches tend to be computationally intensive. We demonstrate the significance of these effects by simulating NSB while accounting for increasingly realistic populations of aerosol components. The use of approximate scattering phase functions reduces computing time while yielding results that reasonably match field observations. This approach can speed up models used to predict NSB while increasing their accuracy.

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Fig. 1: Daylight versus night light: similarities and differences in the range of modelling complexity.
Fig. 2: Aerosol morphology impact on NSB distribution.
Fig. 3: Circumzenithal NSB minima tend to be deeper if spherical shapes dominate the population of atmospheric aerosols.
Fig. 4: Approximate scattering phase functions may compete with exact theories to model NSB.

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Data availability

The numerical results for the all-sky radiance distributions were computed using the model available in ref. 10. The scattering phase functions for dust particles and spherical particles are retrievable in graphical form from ref. 31. Normalized phase functions in digitized form and experimental and computed NSB distributions are available from the corresponding author upon reasonable request. All data that support this study are available in the Supplementary Information.

References

  1. Green, R. F., Luginbuhl, C. B., Wainscoat, R. J. & Duriscoe, D. The growing threat of light pollution to ground-based observatories. Astron. Astrophys. Rev. 30, 1 (2022).

    Article  ADS  Google Scholar 

  2. Kyba, C. C. M. Is light pollution getting better or worse? Nat. Astron. 2, 267–269 (2018).

    Article  ADS  Google Scholar 

  3. Kyba, C. et al. Worldwide variations in artificial skyglow. Sci. Rep. 5, 8409 (2015).

    Article  Google Scholar 

  4. Kyba, C. C. M. et al. Artificially lit surface of Earth at night increasing in radiance and extent. Sci. Adv. 3, e1701528 (2017).

    Article  ADS  Google Scholar 

  5. Barentine, J. C. et al. Skyglow changes over Tucson, Arizona, resulting from a municipal LED street lighting conversion. J. Quant. Spectrosc. Radiat. Transf. 212, 10–23 (2018).

    Article  ADS  Google Scholar 

  6. Hung, L.-W., Anderson, S. J., Pipkin, A. & Fristrup, K. Changes in night sky brightness after a countywide LED retrofit. J. Environ. Manage. 292, 112776 (2021).

    Article  Google Scholar 

  7. Gaston, K. J., Davies, T. W., Bennie, J. & Hopkins, J. Review. Reducing the ecological consequences of night-time light pollution: options and developments. J. Appl. Ecol. 49, 1256–1266 (2012).

    Article  Google Scholar 

  8. Kocifaj, M. & Barentine, J. C. Air pollution mitigation can reduce the brightness of the night sky in and near cities. Sci. Rep. 11, 14622 (2021).

    Article  ADS  Google Scholar 

  9. Aubé, M. Physical behaviour of anthropogenic light propagation into the nocturnal environment. Philos. Trans. R. Soc. B 370, 20140117 (2015).

    Article  Google Scholar 

  10. Kocifaj, M. Multiple scattering contribution to the diffuse light of a night sky: a model which embraces all orders of scattering. J. Quant. Spectrosc. Radiat. Transf. 206, 260–272 (2018).

    Article  ADS  Google Scholar 

  11. Duriscoe, D., Luginbuhl, C. & Elvidge, C. The relation of outdoor lighting characteristics to sky glow from distant cities. Light. Res. Technol. 46, 35–49 (2014).

    Article  Google Scholar 

  12. Kocifaj, M., Kundracik, F., Duriscoe, D. M., Balm, S. P. & Wallner, S. Using ground-based measurements to recover the spectra of radiation escaping from distant light-pollution sources. MNRAS 506, 2739–2745 (2021).

    Article  ADS  Google Scholar 

  13. Lamphar, H., Wallner, S. & Kocifaj, M. Modelled impacts of a potential light emitting diode lighting system conversion and the influence of an extremely polluted atmosphere in Mexico City. Environ. Plan. B Urban Anal. City Sci. 49, 501–518 (2021).

    Article  Google Scholar 

  14. Horvath, H. Basic optics, aerosol optics, and the role of scattering for sky radiance. J. Quant. Spectrosc. Radiat. Transf. 139, 3–12 (2014).

    Article  ADS  Google Scholar 

  15. Louedec, K. & Urban, M. Ramsauer approach for light scattering on nonabsorbing spherical particles and application to the Henyey–Greenstein phase function. Appl. Opt. 51, 7842–7852 (2012).

    Article  ADS  Google Scholar 

  16. Acosta-Herazo, R., Monterroza-Romero, J., Mueses, M. Á., Machuca-Martínez, F. & Puma, G. L. Coupling the six flux absorption–scattering model to the Henyey–Greenstein scattering phase function: evaluation and optimization of radiation absorption in solar heterogeneous photoreactors. Chem. Eng. J. 302, 86–96 (2016).

    Article  Google Scholar 

  17. Gouesbet, G. Van de Hulst essay: a review on generalized Lorenz–Mie theories with wow stories and an epistemological discussion. J. Quant. Spectrosc. Radiat. Transf. 253, 107117 (2020).

    Article  Google Scholar 

  18. Dlugach, J. M. & Mishchenko, M. I. Effects of nonsphericity on the behavior of Lorenz–Mie resonances in scattering characteristics of liquid-cloud droplets. J. Quant. Spectrosc. Radiat. Transf. 146, 227–234 (2014).

    Article  ADS  Google Scholar 

  19. Mishchenko, M. I., Travis, L. D., Kahn, R. A. & West, R. A. Modeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids. J. Geophys. Res. Atmos. 102, 16831–16847 (1997).

    Article  ADS  Google Scholar 

  20. Lin, W., Bi, L. & Dubovik, O. Assessing superspheroids in modeling the scattering matrices of dust aerosols. J. Geophys. Res. Atmos. 123, 13917–13943 (2018).

    Article  ADS  Google Scholar 

  21. Dabrowska, D. D. et al. Scattering matrices of Martian dust analogs at 488nm and 647nm. Icarus 250, 83–94 (2015).

    Article  ADS  Google Scholar 

  22. Lee, R. L. & Hernández-Andrés, J. Measuring and modeling twilight’s purple light. Appl. Opt. 42, 445–457 (2003).

    Article  ADS  Google Scholar 

  23. Cinzano, P. Night sky photometry with Sky Quality Meter. Technical report 9, V1.4, ISTIL; http://unihedron.com/projects/darksky/sqmreport_v1p4.pdf (2005).

  24. Pun, C. S. J., So, C. W., Leung, W. Y. & Wong, C. F. Contributions of artificial lighting sources on light pollution in Hong Kong measured through a night sky brightness monitoring network. J. Quant. Spectrosc. Radiat. Transf. 139, 90–108 (2014).

    Article  ADS  Google Scholar 

  25. Kocifaj, M., Solano-Lamphar, H. A. & Videen, G. Night-sky radiometry can revolutionize the characterization of light-pollution sources globally. PNAS 116, 7712–7717 (2019).

    Article  ADS  Google Scholar 

  26. Duriscoe, D. M. Measuring anthropogenic sky glow using a natural sky brightness model. Publ. Astron. Soc. Pac. 125, 1370–1382 (2013).

    Article  ADS  Google Scholar 

  27. Grauer, A. D. & Grauer, P. A. Linking solar minimum, space weather, and night sky brightness. Sci. Rep. 11, 23893 (2021).

    Article  ADS  Google Scholar 

  28. Liu, X. et al. Influences of relative humidity and particle chemical composition on aerosol scattering properties during the 2006 PRD campaign. Atmos. Environ. 42, 1525–1536 (2008).

    Article  ADS  Google Scholar 

  29. Liu, X. et al. Research on the hygroscopic properties of aerosols by measurement and modeling during CAREBeijing-2006. J. Geophys. Res. Atmos. 114, D00G16 (2009).

    Article  Google Scholar 

  30. Day, D. E. & Malm, W. C. Aerosol light scattering measurements as a function of relative humidity: a comparison between measurements made at three different sites. Atmos. Environ. 35, 5169–5176 (2001).

    Article  ADS  Google Scholar 

  31. Nousiainen, T., Muinonen, K. & Räisänen, P. Scattering of light by large Saharan dust particles in a modified ray optics approximation. J. Geophys. Res. Atmos. 108, 4025 (2003).

    Article  ADS  Google Scholar 

  32. Riziq, A. A., Erlick, C., Dinar, E. & Rudich, Y. Optical properties of absorbing and non-absorbing aerosols retrieved by cavity ring down (CRD) spectroscopy. Atmos. Chem. Phys. 7, 1523–1536 (2007).

    Article  ADS  Google Scholar 

  33. Kocifaj, M., Horvath, H. & Gangl, M. Retrieval of aerosol aspect ratio from optical measurements in Vienna. Atmos. Environ. 42, 2582–2592 (2008).

    Article  ADS  Google Scholar 

  34. Peterson, M. Modeling the transmission of optical lightning signals through complex 3-D cloud scenes. J. Geophys. Res. Atmos. 125, e2020JD033231 (2020).

    Article  ADS  Google Scholar 

  35. Heng, K., Morris, B. M. & Kitzmann, D. Closed-form ab initio solutions of geometric albedos and reflected light phase curves of exoplanets. Nat. Astron. 5, 1001–1008 (2021).

    Article  ADS  Google Scholar 

  36. Fu, Q., Thorsen, T. J., Su, J., Ge, J. M. & Huang, J. P. Test of Mie-based single-scattering properties of non-spherical dust aerosols in radiative flux calculations. J. Quant. Spectrosc. Radiat. Transf. 110, 1640–1653 (2009).

    Article  ADS  Google Scholar 

  37. Muinonen, K. & Videen, G. A phenomenological single scatterer for studies of complex particulate media. J. Quant. Spectrosc. Radiat. Transf. 113, 2385–2390 (2012).

    Article  ADS  Google Scholar 

  38. Stelitano, D., Di Girolamo, P., Scoccione, A., Summa, D. & Cacciani, M. Characterization of atmospheric aerosol optical properties based on the combined use of a ground-based Raman lidar and an airborne optical particle counter in the framework of the hydrological cycle in the Mediterranean Experiment – Special Observation Period 1. Atmos. Meas. Tech. 12, 2183–2199 (2019).

    Article  Google Scholar 

  39. Chin, M. et al. Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sun photometer measurements. J. Atmos. Sci. 59, 461–483 (2002).

    Article  ADS  Google Scholar 

  40. Braun, B., Dorgan, J. R. & Chandler, J. P. Cellulosic nanowhiskers: theory and application of light scattering from polydisperse spheroids in the Rayleigh–Gans–Debye regime. Biomacromolecules 9, 1255–1263 (2008).

    Article  Google Scholar 

  41. Wyatt, P. J. Measuring nanoparticles in the size range to 2000 nm. J. Nanopart. Res. 20, 322 (2018).

    Article  ADS  Google Scholar 

  42. Gordon, H. R. Rayleigh–Gans scattering approximation: surprisingly useful for understanding backscattering from disk-like particles. Opt. Express 15, 5572–5588 (2007).

    Article  ADS  Google Scholar 

  43. Lui, C. W., Clarkson, M. & Nicholls, R. W. An approximation for spectral extinction of atmospheric aerosols. J. Quant. Spectrosc. Radiat. Transf. 55, 519–531 (1996).

    Article  ADS  Google Scholar 

  44. Veretennikov, V. V. & Men’shchikova, S. S. Reconstruction of the aerosol microstructure from measurements of light extinction in the atmosphere under restriction of the spectral range. Atmos. Ocean. Opt. 29, 18–26 (2016).

    Article  Google Scholar 

  45. Mishchenko, M. I. & Travis, L. D. Capabilities and limitations of a current FORTRAN implementation of the T-matrix method for randomly oriented, rotationally symmetric scatterers. J. Quant. Spectrosc. Radiat. Transf. 60, 309–324 (1998).

    Article  ADS  Google Scholar 

  46. Draine, B. T. & Flatau, P. J. Discrete dipole approximation for scattering calculations. J. Opt. Soc. Am. A 11, 1491–1499 (1994).

    Article  ADS  Google Scholar 

  47. Korras-Carraca, M. B., Hatzianastassiou, N., Matsoukas, C., Gkikas, A. & Papadimas, C. D. The regime of aerosol asymmetry parameter over Europe, the Mediterranean and the Middle East based on MODIS satellite data: evaluation against surface AERONET measurements. Atmos. Chem. Phys. 15, 13113–13132 (2015).

    Article  ADS  Google Scholar 

  48. Mishchenko, M. I., Travis, L. D. & Macke, A. Scattering of light by polydisperse, randomly oriented, finite circular cylinders. Appl. Opt. 35, 4927–4940 (1996).

    Article  ADS  Google Scholar 

  49. Puschnig, J., Wallner, S. & Posch, T. Circalunar variations of the night sky brightness – an FFT perspective on the impact of light pollution. MNRAS 492, 2262–2637 (2020).

    Article  Google Scholar 

  50. Korras-Carraca, M. B., Gkikas, A., Matsoukas, C. & Hatzianastassiou, N. Global clear-sky aerosol speciated direct radiative effects over 40 years (1980–2019). Atmosphere 12, 1254 (2021).

    Article  ADS  Google Scholar 

  51. Mishchenko, M. I. Electromagnetic scattering by nonspherical particles: a tutorial review. J. Quant. Spectrosc. Radiat. Transf. 110, 808–832 (2009).

    Article  ADS  Google Scholar 

  52. Fiorentin, P., Cavazzani, S., Ortolani, S., Bertolo, A. & Binotto, R. Instrument assessment and atmospheric phenomena in relation to the night sky brightness time series. Measurement 191, 110823 (2022).

    Article  Google Scholar 

  53. Nousiainen, T., Zubko, E., Lindqvist, H., Kahnert, M. & Tyynelä, J. Comparison of scattering by different nonspherical, wavelength-scale particles. J. Quant. Spectrosc. Radiat. Transf. 113, 2391–2405 (2012).

    Article  ADS  Google Scholar 

  54. Liu, L. et al. Optical properties of morphologically complex black carbon aerosols: effects of coatings. J. Quant. Spectrosc. Radiat. Transf. 281, 108080 (2022).

    Article  Google Scholar 

  55. Tiwari, S. et al. Study of the carbonaceous aerosol and morphological analysis of fine particles along with their mixing state in Delhi, India: a case study. Environ. Sci. Pollut. Res. 22, 10744–10757 (2015).

    Article  Google Scholar 

  56. Shao, L. et al. Morphology, composition and mixing state of individual airborne particles: effects of the 2017 Action Plan in Beijing, China. J. Clean. Prod. 329, 129748 (2021).

    Article  Google Scholar 

  57. Kundracik, F., Kocifaj, M., Videen, G. & Markoš, P. Optical properties of charged nonspherical particles determined using the discrete dipole approximation. J. Quant. Spectrosc. Radiat. Transf. 254, 107245 (2020).

    Article  Google Scholar 

  58. Samset, B. H. et al. Aerosol absorption: progress towards global and regional constraints. Curr. Clim. Change Rep. 4, 65–83 (2018).

    Article  Google Scholar 

  59. Shen, L. et al. Characterizing regional aerosol pollution in central China based on 19 years of MODIS data: spatiotemporal variation and aerosol type discrimination. Environ. Pollut. 263, 114556 (2020).

    Article  Google Scholar 

  60. Mishchenko, M. I. Electromagnetic Scattering by Particles and Particle Groups: An Introduction (Cambridge Univ. Press, 2014); https://www.cambridge.org/core_title/gb/321854

    Book  Google Scholar 

  61. Li, L. et al. Studying aerosol light scattering based on aspect ratio distribution observed by fluorescence microscope. Opt. Express 25, A813–A823 (2017).

    Article  ADS  Google Scholar 

  62. Matsuki, A. et al. Cloud processing of mineral dust: direct comparison of cloud residual and clear sky particles during AMMA aircraft campaign in summer 2006. Atmos. Chem. Phys. 10, 1057–1069 (2010).

    Article  ADS  Google Scholar 

  63. Li, L. I. et al. Effects of the shape distribution of aerosol particles on their volumetric scattering properties and the radiative transfer through the atmosphere that includes polarization. Appl. Opt. 58, 1475–1484 (2019).

    Article  ADS  Google Scholar 

  64. Mishra, S. K. et al. Morphology of atmospheric particles over semi-arid region (Jaipur, Rajasthan) of India: implications for optical properties. Aerosol Air Qual. Res. 15, 974–984 (2015).

    Article  Google Scholar 

  65. Mishchenko, M. I. & Travis, L. D. Light scattering by polydispersions of randomly oriented spheroids with sizes comparable to wavelengths of observation. Appl. Opt. 33, 7206–7225 (1994).

    Article  ADS  Google Scholar 

  66. Schafer, J. S. et al. Intercomparison of aerosol single-scattering albedo derived from AERONET surface radiometers and LARGE in situ aircraft profiles during the 2011 DRAGON-MD and DISCOVER-AQ experiments. J. Geophys. Res. Atmos. 119, 7439–7452 (2014).

    Article  ADS  Google Scholar 

  67. Tang, J. et al. Positive relationship between liquid cloud droplet effective radius and aerosol optical depth over Eastern China from satellite data. Atmos. Environ. 84, 244–253 (2014).

    Article  ADS  Google Scholar 

  68. Zhao, H. et al. Climatological variations in aerosol optical depth and aerosol type identification in Liaoning of Northeast China based on MODIS data from 2002 to 2019. Sci. Total Environ. 781, 146810 (2021).

    Article  ADS  Google Scholar 

  69. Randles, C. A. et al. The MERRA-2 aerosol reanalysis, 1980 onward. Part I: system description and data assimilation evaluation. J. Clim. 30, 6823–6850 (2017).

    Article  ADS  Google Scholar 

  70. Volten, H. et al. Scattering matrices of mineral aerosol particles at 441.6 nm and 632.8 nm. J. Geophys. Res. 106, 17375–17401 (2001).

    Article  ADS  Google Scholar 

  71. Tai, H., Zhuang, Z., Jiang, L. & Sun, D. Visibility measurement in an atmospheric environment simulation chamber. Curr. Opt. Photonics 1, 186–195 (2017).

    Google Scholar 

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Acknowledgements

This work was supported by the Slovak Research and Development Agency under contract no. APVV-18-0014. Computational work was supported by the Slovak National Grant Agency VEGA (grant no. 2/0010/20). This work is part of the project for which the financial means was provided by the European Union’s Horizon 2020 Research and Innovation Programme on the basis of the Grant Agreement under the Marie Skłodowska-Curie funding mechanism no. 945478 - SASPRO 2.

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Authors and Affiliations

  1. ICA, Slovak Academy of Sciences, Bratislava, Slovak Republic

    M. Kocifaj, L. Kómar, H. Lamphar & and S. Wallner

  2. Faculty of Mathematics, Physics, and Informatics, Comenius University, Mlynská Dolina, Bratislava, Slovak Republic

    M. Kocifaj

  3. Dark Sky Consulting, LLC, Tucson, AZ, USA

    J. Barentine

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Contributions

M.K. designed and performed the research. L.K. conducted Mie, T-matrix and discrete dipole approximation computations, while M.K. computed all-sky radiance using MSOS-LP1 and analysed and interpreted the results obtained. H.L. processed the data graphically, S.W. performed field experiments and J.B. reviewed and commented on findings. M.K., J.B. and S.W. wrote the paper.

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Correspondence to M. Kocifaj.

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Nature Astronomy thanks Stefano Cavazzani, Johannes Puschnig and Jessica Arnold for their contribution to the peer review of this work.

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Kocifaj, M., Kómar, L., Lamphar, H. et al. A systematic light pollution modelling bias in present night sky brightness predictions. Nat Astron 7, 269–279 (2023). https://doi.org/10.1038/s41550-023-01916-y

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