We created yearly ALAN measures for all US contiguous counties between 2012 and 2019, and reported substantial variation in both the geographical distribution of and temporal trend in ALAN during this period. As expected, average levels of ALAN were higher in large metropolitan areas and coastal regions, and strongly correlated with GDP and population size. During this period, although the ALAN at the national level decreased slightly since 2012, there existed considerable differences in ALAN trend over time across the country. Several rural counties in Texas experienced remarkable increase in ALAN, while substantial increases in population exposure to ALAN were also observed in many metropolitan areas. Overall, changes in GDP and population size were important predictors of ALAN change, but the majority of variability in county-level ALAN trends were not explained by these two variables. Finally, we found that counties with the highest concentration of minority groups, especially Hispanics, experienced the least decrease in ALAN levels. As a result, racial/ethnic disparities in ALAN have grown wider since 2014 across the US.
A number of earlier studies examined geographical distributions of ALAN levels globally and in the US. (Falchi, Cinzano et al. 2016, Kyba, Kuester et al. 2017, Falchi, Furgoni et al. 2019, Elvidge, Hsu et al. 2020) Like ours, most of these used data from the VIIRS DNB, which provides calibrated, high-resolution nighttime images with large dynamic range. At least one study (Falchi et al. 2019) examined county-level ALAN in the US using 2014 VIIRS observations. Although the study used a somewhat different measure of ALAN (light flux from emitting sources), it produced county rankings of ALAN levels almost identical to ours. The study also revealed a dramatic difference (200,000 fold) between counties with the highest and lowest levels of ALAN, an estimate similar to that observed in our study (102,744-fold difference in average ALAN levels comparing Washington DC to Carton, New Mexico). Beside average ALAN, we also estimated population-level exposure to ALAN, a metric often used to assess public health impact of environmental contaminants such as air pollution, (Moschandreas 2011) and reported a ~ 260,000-fold difference comparing counties with the highest and lowest population exposure (Cook, Illinois and Petroleum, Montana, respectively). Such vast differences in ALAN exposures suggest that the population-level health risks associated with ALAN are likely to vary wildly across the country.
Although our study, to the best of our knowledge, is the first to provide comprehensive data on ALAN temporal changes at the county level in the US, several previous studies estimated changes in ALAN in different world regions. For example, one paper summarized older studies using data from various sources to estimate ALAN change in the second half of the 20th century, and showed an annual increase rate between 2.5% and 19% in several urban areas in USA, Europe, Asia and Central America. (Hölker, Moss et al. 2010) A more recent analysis by Kyba et al. estimated that the global expansion of artificially lit outdoor area was at an annual rate of 2.2% between 2012 and 2016, and for continuously lit areas (defined as average ALAN (2012–2016) ≥ 5 nW/cm2/sr), the level of brightness on average also increased by 2.2% per year. (Kyba, Kuester et al. 2017) Interestingly, this paper found that the US had a stable trajectory in ALAN during this period, along with a few other high-income countries in the Europe. We also found a largely stable and slightly downward trend in national ALAN level; however, this average trend does not reveal the substantial differences in ALAN temporal changes across different counties. Moreover, it is worth noting that patterns in changes in ALAN and in population-level ALAN burden were drastically different, with the latter largely influenced by population size. This difference is important to consider because different metrics of change may have different clinical and public health implications. For example, in rural areas such as Loving, Texas, the tremendous increase in ALAN levels may have a large impact on each individual in spite of the small population size. On the other hand, in more populated areas such as Los Angeles, California, even a small increase in ALAN levels may have a sizable public health impact due to its sheer population size.
It is well established that ALAN is an indicator of economic and population growth. (Levin, Kyba et al. 2020) As expected, we found positive correlation between changes in ALAN and changes in GDP and population size at the county level. However, we also found that trends in GDP and population only explained less than one fourth of the total variability in temporal trends in ALAN in 2012–2019, suggesting other factors are in play. For example, we found that many rural counties in Texas experienced dramatic increase in ALAN, and this pattern is most likely to be explained by increases in oil and gas drilling activities, particularly the bright light emitted from gas flare.(Elvidge and Zhizhin 2021) The identification of specific driving force underlying temporal changes is critical to developing ALAN surveillance programs and policy interventions.
Decades of EJ research has long documented disproportionately high exposure levels to many environmental pollutants in disadvantaged populations. A recent EJ analysis using a one-time measurement of ALAN in 2014 reported that minority populations in the US had a higher population-weighted mean exposure to light pollution when compared to non-Hispanic White Americans. We expanded this line of research by, for the first time, reporting different trajectories of ALAN across counties with different racial/ethnic compositions. Counties with the highest concentration of white populations experienced the most rapid decline in ALAN, while counties with higher % of minority populations, particularly Hispanic populations, experienced significantly less decline between 2012 and 2019. This finding suggests that for disparities in ALAN are dynamic and thus characterizing temporal changes is key to a better understanding and predicting ALAN burdens across the population. The widening gaps in racial/ethnic disparities in ALAN is alarming and warrant further investigation. In particular, future studies should focus on identifying underlying contributing factors and quantifying the potential economic, social, and public health implications of ALAN disparities.
Growing attention has been directed to negative impacts of light pollution on energy consumption, greenhouse gas emission, ecology, evolution, and human health. The US Energy Information Administration estimated that in 2021 lighting accounts for about 5% of total US electricity consumption, (Duncan, Geigert et al. 2018) and efforts in curbing light pollution often point to reducing energy expenditure and cost as a main motivation to develop more efficient artificial lighting. However, the emphasis on energy expenditure of lighting technology alone ignores the myriad unintended consequences of lighting itself. Almost all species on Earth possess an endogenous circadian timing system, which plays a critical role in orchestrating numerous biological processes and represent a fundamental adaptation to the 24-hour cycle of natural lighting environment on our planet. (Albrecht 2010) Light pollution alternates the natural light-and-dark cycle, disrupts circadian rhythms, and has been shown to have adverse effects on the survival, reproduction, migration, communication and general health and well-being of many taxa, including both nocturnal and diurnal organisms. (Jägerbrand and Bouroussis 2021)
In humans, pervasive exposure to ALAN suppresses melatonin, a key hormone in circadian regulation, and enables nighttime activities that are misaligned with the internal circadian clock.(Lunn, Blask et al. 2017) Both melatonin suppression and misaligned nighttime activities can lead to circadian disruption and sleep deficiencies, which are important risk factors for a wide range of adverse health outcomes. (Roenneberg and Merrow 2016) Epidemiological studies have linked excessive ALAN with a wide range of health conditions, (Lunn, Blask et al. 2017, Mason, Boubekri et al. 2018) including mental disorders,(Paksarian, Rudolph et al. 2020) weight gain, (Park, White et al. 2019) obesity risk, (Zhang, Jones et al. 2020) postmenopausal breast cancer,(Hurley, Goldberg et al. 2014, James, Bertrand et al. 2017, Xiao, James et al. 2020, Xiao, Gierach et al. 2021) and pancreatic, thyroid and prostate cancers. (Kim, Lee et al. 2017, Xiao, Jones et al. 2021, Zhang, Jones et al. 2021) Although the observational nature of these epidemiological investigations makes it challenging to establish causal relationships between ALAN and health outcomes, a role of ALAN in disease risk is further supported by numerous laboratory studies in both animal models and human subjects that convincingly showed a mechanistic link between misaligned light exposure, circadian disruption, and adverse health effects. (Opperhuizen, Stenvers et al. 2017, Fleury, Masis-Vargas et al. 2020, Mason, Grimaldi et al. 2022) Taken together, ALAN is an important environmental exposure with important consequences in public health and other areas, and thus it is imperative to generate comprehensive and up-to-date ALAN data to enable better assessment of population burden of ALAN exposure.
It is worth noting that although there are significant implications of our current analysis, an important limitation of mapping ALAN using satellite imagery in the context of public health is the uncertainty about how well satellite-based ALAN estimates capture actual light exposure experienced at the individual level. Satellite-based measures are primarily driven by outdoor ALAN levels, and may not accurately reflect indoor light exposure that has a larger and more direct health impact for most individuals. Indeed, two previous studies reported minimal correlation between the satellite-based estimates and individual-level measures of LAN.(Rea, Brons et al. 2011, Huss, van Wel et al. 2019) Moreover, the validity of using satellite-based LAN estimate as a proxy measure of individual-level LAN exposure can be influenced by individual lifestyle and occupational factors (e.g., window treatment, sleep habits, nighttime social activities, shift work), and can vary among groups with different sociodemographic and geographic characteristics. Therefore, the field will benefit from large-scale validation study aimed at comparing satellite-based estimate of LAN with individual-level measures, and in-depth investigation about how population attributes may influence the validity of satellite-based LAN measure in the context of public health research.
In summary, our analysis demonstrated substantial differences in both geographic distribution and temporal trends of ALAN in US counties. The results also highlighted evolving disparities in ALAN exposure across different racial/ethnic groups. Given the broad implications of ALAN, including its well-established public health consequences, future studies should closely monitor ALAN exposure, evaluate attributable health burdens, and provide evidence for developing targeted policies to ameliorate negative societal impact by ALAN.