Abstract: The visual brightness of the night sky is not a single-valued function of its brightness in other photometric bands, because the transformations between photometric systems depend on the spectral power distribution of the skyglow. We analyze the transformation between the night sky brightness in the Johnson-Cousins V band (mV, measured in magnitudes per square arcsecond, mpsas) and its visual luminance (L, in SI units cd m−2) for observers with photopic and scotopic adaptation, in terms of the spectral power distribution of the incident light. We calculate the zero-point luminances for a set of skyglow spectra recorded at different places in the world, including strongly light-polluted locations and sites with nearly pristine natural dark skies. The photopic skyglow luminance corresponding to mV = 0.00 mpsas is found to vary between 1.11–1.34 × 105 cd m−2 if mV is reported in the absolute (AB) magnitude scale, and between 1.18–1.43 × 105 cd m−2 if a Vega scale for mV is used instead. The photopic luminance for mV = 22.0 mpsas is correspondingly comprised between 176 and 213 μcd m−2 (AB), or 187 and 227 μcd m−2 (Vega). These constants tend to decrease for increasing correlated color temperatures (CCT). The photopic zero-point luminances are generally higher than the ones expected for blackbody radiation of comparable CCT. The scotopic-to-photopic luminance ratio (S/P) for our spectral dataset varies from 0.8 to 2.5. Under scotopic adaptation the dependence of the zero-point luminances with the CCT, and their values relative to blackbody radiation, are reversed with respect to photopic ones.

Abstract: The emission spectrum of a light-pollution source is a determining factor for modelling artificial light at night. The spectral composition of skyglow is normally derived from the initial spectra of all artificial light sources contributing to the diffuse illumination of an observation point. However, light scattering in the ambient atmosphere imposes a wavelength-specific distortion on the optical signals captured by the measuring device. The nature of the emission, the spectra and the light-scattering phenomena not only control the spectral properties of the ground-reaching radiation, but also provide a unique tool for remote diagnosis and even identification of the emission spectra of the light-polluting sources. This is because the information contained in the night-sky brightness is preferably measured in directions towards a glowing dome of light over the artificial source of light. We have developed a new method for obtaining the emission spectra using remote terrestrial sensing of the bright patches of sky associated with a source. Field experiments conducted in Vienna and Bratislava have been used to validate the theoretical model and the retrieval method. These experiments demonstrate that the numerical inversion is successful even if the signal-to-noise ratio is small. The method for decoding the emission spectra by the light-scattering spectrometry of a night sky is a unique approach that enables for (i) a systematic characterization of the light-pollution sources over a specific territory, and (ii) a significant improvement in the numerical prediction of skyglow changes that we can expect at observatories.

Abstract: Light pollution poses a growing threat to optical astronomy, in addition to its detrimental impacts on the natural environment, the intangible heritage of humankind related to the contemplation of the starry sky and, potentially, on human health. The computation of maps showing the spatial distribution of several light pollution related functions (e.g. the anthropogenic zenithal night sky brightness, or the average brightness of the celestial hemisphere) is a key tool for light pollution monitoring and control, providing the scientific rationale for the adoption of informed decisions on public lighting and astronomical site preservation. The calculation of such maps from satellite radiance data for wide regions of the planet with sub-kilometric spatial resolution often implies a huge amount of basic pixel operations, requiring in many cases extremely large computation times. In this paper we show that, using adequate geographical projections, a wide set of light pollution map calculations can be reframed in terms of two-dimensional convolutions that can be easily evaluated using conventional fast Fourier-transform (FFT) algorithms, with typical computation times smaller than 10^-6 s per output pixel.