Beyond the Clouds: Advanced Data Analysis of a Dutch Sky Quality Meter Network

TL;DR

This study analyzes long-term light pollution data from Dutch and German regions using sky quality meters and cloud data, revealing increasing brightness trends, variability patterns, and sources of artificial light pollution to inform mitigation efforts.

Contribution

It introduces a comprehensive analysis combining SQM measurements and cloud data over multiple years, highlighting spatial and temporal patterns of light pollution in the region.

Findings

Dark areas show higher variability in brightness.

Light pollution is increasing at 2.78 to 6.68% annually in darkest zones.

Artificial sources dominate in brighter areas, reducing natural light influence.

Abstract

Light pollution is an increasing environmental concern, impacting both ecological systems and human health. This report presents an analysis of light pollution data from the washetdonker.nl SQM network from 2020 until 2023, with a focus on indirect light pollution, commonly known as skyglow. By integrating measurements from Sky Quality Meter (SQM) stations in the network and cloud cover data from EUMETSAT, we conducted a comprehensive analysis of night sky brightness across a region encompassing northern Netherlands and the western part of the German Wadden Coast. Yearly changes in brightness for 27 locations were ranked and plotted, revealing that in the darkest areas, light pollution is increasing at a rate of 2.78 to 6.68 percent per year. A trend emerged showing that brighter areas experienced lower variability in brightness, while darker zones exhibited higher variability. This is due to the dominance of artificial light sources, such as street lighting, in brighter areas, which reduces the influence of natural light sources like the Moon, stars, and cloud backscatter. Seasonal patterns and the effects of the Milky Way were also investigated. Density plots were employed to visualize these changes in night sky brightness, helping to identify specific sources of light pollution, such as greenhouse lighting and streetlight turn-off times. These findings emphasize the need for systematic monitoring of light pollution and offer valuable insights that can guide public awareness initiatives and inform light pollution mitigation strategies.