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Article

The Ecological Economics of Light Pollution: Impacts on Ecosystem Service Value

by
Sharolyn J. Anderson
1,2,*,
Ida Kubiszewski
1,3 and
Paul C. Sutton
2,4
1
Crawford School of Public Policy, Australian National University, Canberra, ACT 2601, Australia
2
Business School, University of South Australia, Adelaide, SA 5001, Australia
3
Institute for Global Prosperity, University College London, London WC1E 6BT, UK
4
Department of Geography and the Environment, University of Denver, Denver, CO 80208, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(14), 2591; https://doi.org/10.3390/rs16142591
Submission received: 15 March 2024 / Revised: 13 June 2024 / Accepted: 27 June 2024 / Published: 15 July 2024
(This article belongs to the Special Issue Remote Sensing and GIS Technologies for Sustainable Ecosystem Management)
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Abstract

:
Light pollution has detrimental impacts on wildlife, human health, and ecosystem functions and services. This paper explores the impact of light pollution on the value of ecosystem services. We use the Simplified All-Sky Light Pollution Ratio (sALR) as a proxy for the negative impact of light pollution and the Copernicus PROBA-V Global Landcover Database as our proxy of ecosystem service value based on previously published ecosystem service values associated with a variety of landcovers. We use the sALR value to ‘degrade’ the value of ecosystem services. This results in a 40% reduction in ecosystem service value in those areas of the world with maximum levels of light pollution. Using this methodology, the estimate of the annual loss of ecosystem service value due to light pollution is USD 3.4 trillion. This represents roughly 3% of the total global value of ecosystem services and 3% of the global GDP, estimated at roughly USD 100 trillion in 2022. A summary of how these losses are distributed amongst the world’s countries and landcovers is also presented.

1. Introduction

Light pollution is increasingly recognized as a threat to human health and wellbeing in addition to constituting a growing threat to wildlife and many ecosystem functions and services. Despite these recognized problems, light pollution is increasing by 2–10% per year [1,2]. This is despite (and occasionally because of) new technology aimed at reducing light pollution (e.g., LEDs) [3]. The natural night sky is the resource affected by light pollution. Effective stewardship of natural night skies is a challenging problem at the nexus of science, policy, communication, coalition building, monitoring, and enforcement. Night skies that are not impacted by anthropogenic light are a characteristic of functioning ecosystems. The ecosystem services provided by these functioning ecosystems are degraded by anthropogenic light [4]. There is growing recognition that light pollution represents an unrecognized challenge for ecosystem service research and management [5,6,7].

1.1. Human Health Impacts of Light Pollution

Research on artificial light at night (ALAN) and the impacts of the loss of natural night-time light cycles on humans includes studies on shiftwork, health, wellbeing, and sleep [8,9,10,11,12]. One paper reviewed the epidemiological and experimental impacts of light pollution on human health [13]. Light pollution has significant impacts on humans. Evidence from controlled experimental studies shows that nocturnal light exposure impacts our visual system, disrupts our circadian physiology, suppresses melatonin production, and causes sleep disorders [14,15]. There is growing evidence that nocturnal light pollution causes increased levels of chronic diseases including breast cancer, obesity, and diabetes [16,17]. For a more complete review of the human health impacts of light pollution, see [18,19,20,21,22]. Due to the minimal research to date in the area of light pollution and human health, there is a strong need for incorporating more stringent protocols and research [23].

1.2. Ecological Impacts of Light Pollution

Sanders et al. [23] showed that light pollution causes a broad array of impacts for non-human organisms. Diurnal cycles have been a significant environmental reality for virtually all of human and non-human evolution. We are only beginning to understand the impacts of light pollution and its associated problems while acknowledging that these effects on natural ecosystems are highly variable and complex [7]. Light pollution impacts vegetation [24,25]. In another study, Solano-Lamphar and Kocifaj modeled skyglow and found that some types of artificial light at night can have effects on plant photoreceptors, in addition to affecting a plant’s phenology [26]. In Australia, the nocturnal migration of the bogong moth and the alarming decline of moths migrating to the Australian Alps is a complex problem, but one of the factors is light pollution [27]. Marine and coastal area effects include seabird and sea turtle hatchling navigation, predation patterns, failed coral spawning synchronization, and even inhibition of certain zooplanktons [6]. Ongoing research is developing frameworks for evaluating the impacts of light pollution on global protected areas [28]. Our understanding of the ecological impacts of light pollution are nascent and growing, including how there are differential impacts of light pollution depending on ecosystem [29]. This suggests that we conduct assessments on the lost value of natural night skies.

1.3. Light Pollution as a Negative Impact on an Ecosystem’s Service Value

This research explores the role that natural night skies have in an ecosystem’s service value. An extensive number of valuation studies on ecosystem services explicitly ignored or failed to include the impacts of light pollution. The values determined in these studies may have included light pollution implicitly but did not account for spatial variability in the quality and intensity of these impacts. Artificial light at night (ALAN) can have disruptive impacts on ecosystem function [19]. This suggests that a natural ecosystem with no light pollution has a value of ‘x/hectare’, whereas light pollution would be subtracted from ‘x/hectare’ depending on the spatial extent and intensity. Incorporation of sensory resources (visual, auditory, and olfactory) as positive or negative impacts on ecosystem services is not documented clearly in existing studies.
Public understanding of the value and importance of natural night skies is often recognized at the personal level. However, the public does not perceive the aforementioned qualities of these sensory resources. We need an improved approach to communicating the importance of these sensory resources to the public. This research provides an estimate of the lost value of ecosystem services caused by light pollution.

2. Data and Methods

2.1. Data

Our baseline ecosystem service value dataset was derived from the same methodology used by Costanza et al. [30]. Here, we treat light pollution in a similar manner to land degradation, namely as an impact on the value of ecosystem services [31]. The global landcover dataset used in this particular study was obtained from the European Space Agency. The landcover characteristics provided 23 landcover classes at a 100 m spatial resolution. A description of the image processing and calibration of this dataset was provided by Sterckx et al. [32]. These 23 landcover classes were aggregated to broader categories based on available matching ecosystem service value categories from previous research [30]. Some ecosystem service values associated with these landcovers were updated using an updated version of the TEEB table [30]. The ecosystem service values and aggregated landcovers are presented in Table 1.
Light pollution manifests in many ways. There are 6800-fold differences between the most polluted and least polluted areas across Europe [33]. It consists of several components, including glare, trespass, skyglow, clutter. Here, we use a spatially explicit model of skyglow. This skyglow model serves as a proxy measure of many different combinations of the components of light pollution. We recognize that there is a difference between astronomical and ecological light pollution [34]. Astronomical light pollution impairs Earth surface observation of the skies, whereas ecological light pollution refers to the infiltration of point sources of light into local marine and terrestrial environments.
The simplified All-Sky Light Pollution Ratio (sALR) measures the amount of artificial light in the night sky compared with natural starlight, providing a clear indication of light pollution. Higher sALR values indicate greater light pollution, which can obscure stars and celestial objects, affecting astronomical observations and ecosystems. This metric helps in assessing and mitigating the impacts of artificial lighting on the environment and human health. A value of 1.0 is twice as bright as a natural night sky, while a value of 10 is 10 times brighter than a natural night sky. The spatially explicit impact of artificial light at night (ALAN) was represented by the Simplified All-Sky Light Pollution Ratio (sALR) [35], derived from the VIIRS DNB annual composite for the year 2020 [36]. The sALR is different than the commonly used the New World Atlas of Artificial Night Sky Brightness [37] in that it accounts for sky brightness from all directions. Simply put, this includes skyglow from the horizon at all locations. Additional data used in the analysis include the population data for each country, which were extracted from the GHSL 2020 dataset using the Global Human Settlement Layer (GHSL) population density map from 2020 [38]. The country boundaries were obtained from the World Bank [39] (list of source data in Supplementary Materials).

2.2. Methods

We used a sALR of 10 to establish a threshold for the maximum light pollution impact on the ecosystem service value. We arrived at the value of 10 because that is the level at which the Milky Way disappears [35]. The disappearance of the Milky Way impacts insects (e.g., dung beetles) and avian species [40,41]. We used a reclassified version of the sALR such that all values greater than 10 were set to a value of 10. We chose this threshold to represent the maximum degradation of the ecosystem service value. The formula below uses this reclassified sALR (RCsALR) as follows:
Light Pollution Degraded ESV = BaseESV × [0.6 + (0.4 × (1 − (RCsALR/10)))]
This equation preserves 60% of the ecosystem service value in the most light-polluted areas, with a continuous linear increase in the ecosystem service value reaching a 100% pristine state at an sALR of 0.0. The RCsALR ranges from 0.0 for a clear night sky to 10 at light pollution levels in which the Milky Way is not discernible. This results in a 40% reduction in the ecosystem service value in those areas of the world with maximum levels of light pollution.
We acknowledge that this approach to estimating the impact of light pollution on the ecosystem service value is an oversimplification of what is undoubtedly a complex and spatially variable phenomenon. Most of Earth’s surface is not directly affected by light pollution (over 77% of Earth’s sALR is less than 0.05). We acknowledge that light pollution is impacting areas of the earth that have no direct light pollution (e.g., bogong moth migration and bird migration) [36]. Varying levels of light pollution will have differential impacts on species, habitats, and human health. Our approach is an oversimplification of complex and variable phenomena. We suggest that the highest levels of light pollution are predominantly in urban areas, with significant impacts on human health due to high population densities. We posit that the negative externalities of light pollution affecting human health in urban areas degrade those ecosystem services by 40%. Light pollution in exurban areas [35] with a mix of wildlife and humans tend to have lower percentages of degradation in their ecosystem service values. This resulted in a global ESV grid degraded by the extent and intensity of light pollution (Figure 1).
We selected an area of Australia that is home to the first National Park City in the Southern Hemisphere (https://www.nationalparkcity.org/ accessed on 1 July 2024). The National Park City is a global movement of urban areas that are bringing the natural world to their residents. In addition, this area has the first Australian certified dark sky reserve and one of only 15 in the world. These designations and commitment to the environment were the reasons that this area was selected as the area of interest for Figure 2. The landcover, ESV, and light pollution-degraded ESV are presented for the Adelaide and Kangaroo Island regions of South Australia (Figure 2). The center image shows the ocean as having a relatively low ecosystem service value (USD 660/ha). Skyglow from the city of Adelaide degrades those marine areas at different rates as a function of the distance, resulting in the lowest (darkest) ecosystem service values in the image on the right. We used GIS functions to sum the original natural ESV for each landcover and for each country in the world. We then summarized the light pollution-degraded ESV for each landcover and country in the world. Using these data products, we determined the extent of loss in ESV from light pollution by both land cover and country (Supplementary Materials).

3. Results and Discussion

Light pollution decreased global ESVs by USD 3.36 Trillion/year (Table 2). This represents 3% of the total global ESV when using the landcover-specific ecosystem service values with this global landcover dataset. Geographic partitioning of these impacts is thought-provoking. As one would expect, urban areas had the highest percentage losses in ESVs due to light pollution being at 20% (Table 2). Urban areas had the highest sALR levels because of the social and economic development associated with higher population densities. The highest aggregate losses in ESVs were for the following landcovers: grasslands (USD 418 billion), croplands (USD 480 billion), and wetlands (USD 1.3 trillion).
Partitioning ESV losses by country painted a different picture (Figure 3). For all of the numbers, see the country table in Supplementary Materials. Russia (USD 754 billion), the United States (USD 468 billion), Canada (USD 312 billion), China (USD 225 billion), India (USD 110 billion), and Brazil (USD 86 billion) took the top six spots with respect the total annual losses in ESVs due to light pollution. The top non-island countries on a per capita basis were Canada (USD 8416 per person per year), Russia (USD 5187 per person per year), Iceland (USD 3837 per person per year), Finland (USD 2561 per person per year), and Norway (USD 1553 per person per year). Sorting this table by percent loss in ESV ranked many island and small coastal nations at the top. These percentage losses in ESVs ranged from 35 to 40 percent. The exceptions were islands and countries of extreme northern or southern latitudes. For example, Svalbard’s data were influenced by aurora borealis lighting, which is not artificial light at night.
This work was motivated by the idea expressed by the Florida Department of Fish and Wildlife:
‘Short of a thorough discussion on the ecological place of sea turtles, it is sufficient to say that the world would be a poorer place to live without them. We just don’t know how much poorer’ [42].
We engaged in this research to raise awareness and action so that we hopefully do not have to find out. This work supports the plea for development of dark infrastructure for the preservation of biodiversity [43] and the ecosystem service benefits of biodiversity [44]. Light pollution undoubtedly has a negative impact on an ecosystem’s function and the ecosystem service value. We attempted to quantify the impact of light pollution on the ecosystem service value without elaborating on the myriad spatially and temporally varying ways that ecosystem functions are impacted by light pollution. This is admittedly a rough estimate of the loss in ecosystem service value. Some of these complications manifest in the spatial effects of light pollution. Areas of the world which are completely dark (e.g., experience an ‘excellent dark sky’) may nonetheless suffer impaired ecosystem function and reduced ecosystem service values. For example, bogong moths have migrated from winter breeding grounds throughout Queensland, New South Wales, and Western Victoria to the Victorian Alpine region for more than 7000 years (a known ecological phenomenon). In 2017, the moth numbers crashed from roughly 4 billion to being almost undetectable, and light pollution contributed to this radical disruption of the moths’ migration [45]. Thus, an area with an ‘excellent dark sky’ (the Victorian Alpine region) experienced a degradation in its ecosystem service value. Our model did not capture this ESV degradation. A spatial mismatch of light pollution and ecosystem service value degradation also manifests with the impact of light pollution on sea turtle hatchlings’ ability to reach the sea [46]. Some of these complications manifest in the temporal effects of light pollution. Cloud cover can temporarily increase the impact of skyglow [47]. Our model of ecosystem service value degradation is conservative in that it associates zero degradation with the majority of Earth’s surface which experiences ‘excellent dark skies’. The aforementioned examples demonstrate that many dark areas are nonetheless experiencing impaired ecosystem function and degraded ecosystem service values. We believe our estimates are consequently more likely to be underestimates rather than overestimates. A draft of our rationale for the 40% maximum level of ecosystem service value degradation as a function of the sALR values follows.
Light pollution is a driver of habitat fragmentation [48]. Habitat fragmentation reduces biodiversity by 13–75 percent and impairs key ecosystem functions [49]. A recent experimental study [50] showed that street lighting caused reduced caterpillar abundance by 47% in hedgerows and 33% in grass medians in urban areas. There is growing concern that we are experiencing an insect apocalypse or ‘insectageddon’ in which declining numbers of insects are hollowing out the bottom of the food chain. These and other studies on species (‘Declines in Insect Abundance’ [51]; ‘Insect Decline in the Anthropocene: Death by a Thousand Cuts’ [52]; and ‘Toward a world that values insects’ [53]) suggested to us that using 40% degradation in the ecosystem service value in urban areas was a plausible estimate. Recognition that even ‘excellent dark sky’ areas often suffer from reduced ecosystem service values supports the idea that scaling ecosystem service value degradation down to 0% impact for excellent dark skies is conservative.
This research provides a method for enhancing our ability to understand the significance, spatial distribution, and magnitude of the negative consequences of light pollution. Here, we estimated the dollar value for the impacts of light pollution on an amalgam of complex phenomena (e.g., human health impacts, bird migration, pollination, predator-prey dynamics, and foraging). Critics can argue that this approach is an oversimplification and that assessing these impacts in units of dollars is an act of hubris that serves a neo-liberal agenda of commodifying nature. This is absolutely not the case. The global economy cannot afford to internalize the externalities of light pollution, climate change, loss of biodiversity, nor most of the other grand challenges associated with environmental degradation. Many degraded ecosystems and associated losses of ecosystem services are a result of anthropogenic disservices, such as light pollution. Eliminating the anthropogenic disservice restores ecosystem services which provide benefits while the eliminated disservices lower costs. This research represents a first attempt at quantifying the avoided costs and lost benefits associated with light pollution which are predominantly produced in urban environments.

4. Conclusions

Light pollution has been increasingly recognized by the scientific community as having serious impacts on human health, wildlife, and ecosystem function. There will never be a definitive ‘truth’ about the value of ecosystem services or, consequently, the impact of light pollution on those ecosystem services. The contribution this paper makes is highlighting the fact that light pollution has negative economic impacts in the form of both degraded ecosystem function, which in turn reduces the ecosystem service value, but also in terms of ecosystem disservices associated with negative impacts on human health and wellbeing. This research used a skyglow model to represent light pollution throughout the study with the understanding that light pollution is a combination of ALAN, with skyglow as one component. This single degradation of one of many sensory resources exemplifies our underestimation of the impacts of anthropogenic disservices on our natural environment. This research suggests that losses in ecosystem service value associated with light pollution are to the order of USD 3 trillion/year. Given a global population of 8 billion, we suggest that light pollution costs each of us more than USD 375/year in lost ecosystem services. This research provides a simple scalable approach to quantifying ESV losses due to light pollution. Light pollution, unlike other types of pollution, is easily mitigated. In fact, mitigation can save money, improve health, and restore ecosystem function. Policies aimed at mitigating light pollution are a win-win-win choice in charting a path to a just, sustainable, and desirable future.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/rs16142591/s1.

Author Contributions

Conceptualization, S.J.A., I.K. and P.C.S.; methodology, S.J.A. and P.C.S.; validation, S.J.A., I.K. and P.C.S.; formal analysis, S.J.A.; investigation, S.J.A., I.K. and P.C.S.; data curation, S.J.A.; writing—original draft preparation, S.J.A.; writing—review and editing, S.J.A., I.K. and P.C.S.; visualization, S.J.A.; funding acquisition, I.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original data presented in the study are openly available and can be found in Supplementary Materials.

Conflicts of Interest

The authors declare no conflicts of interest.

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Remotesensing 16 02591 g001
Figure 1. Flowchart of the processing of the ecosystem service value for each of the landcovers and for each country. The processing includes subtracting the ESV 2011 recalculated for this landcover dataset and the degraded value due to light pollution.
Figure 1. Flowchart of the processing of the ecosystem service value for each of the landcovers and for each country. The processing includes subtracting the ESV 2011 recalculated for this landcover dataset and the degraded value due to light pollution.
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Figure 2. Landcover, ecosystem service value (ESV), and light pollution degradation of ESV for a region of South Australia centered on Adelaide.
Figure 2. Landcover, ecosystem service value (ESV), and light pollution degradation of ESV for a region of South Australia centered on Adelaide.
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Remotesensing 16 02591 g003
Figure 3. Dot map of ESV loss by country.
Figure 3. Dot map of ESV loss by country.
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Table 1. Ecosystem service values associated with aggregated PROBA-V Global Landcover Database categories.
Table 1. Ecosystem service values associated with aggregated PROBA-V Global Landcover Database categories.
lcCodeLand CoverESV (US2011$/ha-yr)
0unknown0
20Grassland_Range4166
30Grassland_Range4166
40Cropland5567
50Urban6661
60Deserts586
70Snow_Ice0
80Lakes_Rivers12,512
90Wetlands140,174
100Tundra648
111Boreal3137
112Boreal3137
113Tropical5382
114Boreal3137
115Forest3800
116Forest3800
121Boreal3137
122Tropical5382
123Boreal3137
124Boreal3137
125Forest3800
126Forest3800
200Ocean660
Table 2. ESV losses from light pollution by landcover.
Table 2. ESV losses from light pollution by landcover.
LandcoverBase ES ValueLP Degraded ES ValuePercent Loss Total Loss
Boreal5,863,684,004,4135,719,030,091,7462.5144,653,912,667
Croplands8,291,544,685,0537,811,898,946,8455.8479,645,738,208
Deserts1,188,699,666,8501,169,067,886,2721.719,631,780,578
Forest5,938,223,881,0005,728,574,756,7083.5209,649,124,292
Grasslands16,479,525,483,14616,060,921,565,6942.5418,603,917,452
Gresh water3,941,525,085,0563,769,933,279,9284.4171,591,805,128
Ocean22,271,071,887,24021,959,997,070,9301.4311,074,816,310
Tropical8,161,178,257,4408,075,040,005,8611.186,138,251,579
Tundra91,406,595,52879,563,110,77513.011,843,484,753
Urban786,305,211,981627,927,970,89220.1158,377,241,089
Wetlands32,640,848,534,21831,286,886,809,1094.11,353,961,725,109
Total105,654,013,291,925102,288,841,494,7613.23,365,171,797,164
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Anderson, S.J.; Kubiszewski, I.; Sutton, P.C. The Ecological Economics of Light Pollution: Impacts on Ecosystem Service Value. Remote Sens. 2024, 16, 2591. https://doi.org/10.3390/rs16142591

AMA Style

Anderson SJ, Kubiszewski I, Sutton PC. The Ecological Economics of Light Pollution: Impacts on Ecosystem Service Value. Remote Sensing. 2024; 16(14):2591. https://doi.org/10.3390/rs16142591

Chicago/Turabian Style

Anderson, Sharolyn J., Ida Kubiszewski, and Paul C. Sutton. 2024. "The Ecological Economics of Light Pollution: Impacts on Ecosystem Service Value" Remote Sensing 16, no. 14: 2591. https://doi.org/10.3390/rs16142591

APA Style

Anderson, S. J., Kubiszewski, I., & Sutton, P. C. (2024). The Ecological Economics of Light Pollution: Impacts on Ecosystem Service Value. Remote Sensing, 16(14), 2591. https://doi.org/10.3390/rs16142591

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