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Review

A Review of the Characteristics of Light Pollution: Assessment Technique, Policy, and Legislation

1
Key Laboratory of Micro Opto-Electro Mechanical System Technology, Ministry of Education, Tianjin University, Tianjin 300072, China
2
Tianjin Eco-Environmental Monitoring Center, Tianjin 300191, China
3
Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of Commerce, Tianjin 300134, China
*
Authors to whom correspondence should be addressed.
Energies 2024, 17(11), 2750; https://doi.org/10.3390/en17112750
Submission received: 16 April 2024 / Revised: 27 May 2024 / Accepted: 31 May 2024 / Published: 4 June 2024
(This article belongs to the Topic Thermal Energy Transfer and Storage)

Abstract

:
Light pollution from the use of artificial lighting poses significant impacts on human health, traffic safety, ecological environment, astronomy, and energy use. The advancement of characteristics of light pollution assessment technology has played a significant role in shaping prevention and control policies, thereby enabling measures, such as environmental standards and legislation and product procurement guidelines, but considerable variation in the definition, control strategies, and regulatory frameworks remains. Therefore, there is a need to review the characteristics of light pollution, including the assessment technique, policy, and legislation. Through the literature review, it can be found that technical standards are required to prevent light pollution. For example, light pollution is decreased by 6% in France through the legislation of artificial light. Key approaches are suggested to control global light pollution, including implementing ambient brightness zoning, regulating lighting product usage, and establishing dark sky reserves. Technology and policy should be integrated. The precise data coming from satellite imagery, drones, and balloons could provide guidance when making the policies.

1. Introduction

Artificial illumination has significantly enriched the quality of life by creating luminous environments during the nighttime. As lighting technologies continue to advance, both the positive and negative impacts have become increasingly discernible. The progress in lighting technology offers flexibility, but the improper application of such advancements has given rise to the predicament known as “light pollution” [1]. This phenomenon exerts detrimental effects on both expansive and localized areas, leaving an indelible mark on astronomical research and the ecological balance, thus inflicting irreparable damage upon global ecosystems. At a local level, it is intrinsically intertwined with economic and societal development, adversely affecting humans, animals, and plants [2]. For instance, it disrupts the quality of sleep, impairs vision, compromises immune systems, and even potentially induces cancer. Moreover, it misguides the migratory routes of birds and sea turtles, impedes insect reproduction and vegetation pollination, and results in the wasteful consumption of energy. However, there are some issues that need to be clarified: (1) Although various regions across the globe, including Europe, North America, and Asia, have endeavored to address this issue through rational lighting, energy conservation, emission reduction, and the assessment of light pollution, there exists quite a difference among these regions. It is necessary to conclude and analyze them. (2) There have been some studies in the literature which primarily focus on the technical research aiming at alleviating the negative effects of light pollution. The combination of the integration of technology and policy are needed, as well as the limitations of current policy measures. Therefore, this study aims to bridge this gap by presenting an analysis of light pollution assessment technologies, policies, and the convergence of technology and policy.
To comprehensively explore light pollution, this study posits four fundamental assumptions: (1) Light pollution will intensify as the global economy continues to grow, and artificial lighting becomes more ubiquitous. (2) The concentration of urban populations and the expansion of urban areas will exacerbate the issue of light pollution in emerging economies. (3) Long-standing environmental policies have predominantly addressed concerns related to air, water, and soil pollution. (4) The unequal distribution of light pollution among different social groups suggests that market-based and command-and-control policies yield similar environmental outcomes.
This paper specifically focuses on the assessment of light pollution and policy research, playing a pivotal role in promoting global research on light pollution policies. The key highlights of this article are as follows: (1) An overview of the research progress in light pollution assessment, encompassing seminal literature, simulation models, testing, and evaluation techniques. (2) An exploration of the characteristics of regulatory policies aimed at mitigating light pollution in specific areas, including legislation and the formulation of standards. (3) A discussion on the integration of technologies and policies, along with potential avenues for merging assessment technologies and light pollution control policies, thereby shedding light on emerging trends in light pollution prevention and control.
The subsequent sections of this paper are organized as follows: Section 2 introduces the definition and evaluation technology of light pollution. Section 3 delves into regulatory policies pertaining to light pollution. Section 4 discusses the coherence of policies and the feasibility of integrating technology and policy. Finally, Section 5 concludes the paper.

2. Definition, Classification, Assessment, and Control of Light Pollution

Light pollution research, spanning more than a century, initially concentrated on observing its deleterious effects on biological systems. Over time, these investigations broadened to include ecosystems and human health. The evaluative methodologies in light pollution research have progressed from rudimentary observations to encompass diverse techniques such as measurement, simulation, and analysis of satellite remote sensing imagery [3]. The advancements in evaluation techniques have laid a robust foundation for the formulation and implementation of policy measures. Consequently, initiatives for the prevention and control of light pollution have evolved into comprehensive policy frameworks characterized by regional or national perspectives and multi-faceted approaches [4]. These developments serve as invaluable benchmarks for light environment management globally.

2.1. Definition of Light Pollution

The International Dark Sky Association (IDA) acknowledges light pollution as a significant environmental concern, affecting humans, wildlife, and the climate. It encompasses issues like glare, sky glow, light trespass, and clutter [5]. In contrast, the International Commission on Illumination (CIE) defines light pollution as the cumulative adverse impacts of artificial light [6]. Further classification by Longcore et al. [7] distinguish astronomical light pollution, obscuring stars and celestial bodies due to directed or reflected upward light, and ecological light pollution, disrupting natural light and dark patterns in ecosystems. Narisada et al. [8] characterize light pollution as a negative consequence of artificial outdoor lighting. These varying definitions lead to diverse recommendations [9]. IDA and the Lighting Engineering Society of North America propose the Demonstration Lighting Ordinance (DLO), advocating for different lighting levels from LZ0 (preserving the original natural environment in limited lighting areas) to LZ4 (urban wide development). They emphasize shielded lamps, avoidance of upward lighting, and adherence to TM-15-11 “BUG” (backlight, upper, and glare) guidelines for outdoor lighting lamps [5]. The International Lighting Commission addresses interfering light with the CIE150 document, categorizing the light environment into five usage-based categories [6]. It establishes emission limits for light sources in different areas, including vertical illumination limits for houses, brightness limits for the field of vision, light curtain brightness and threshold increment limits, and the light flux ratio (ULR/UFR) for controlled lighting. Regulations also exist for building facade and logo sign brightness limits [10]. The European standardization committee imposes specific requirements for protecting the night environment. These include using vertical illumination to assess light intrusion into windows, brightness intensity for glare identification, the upward light ratio for determining sky glow from lighting devices, and observer perception of building brightness, detailed in Table 1 [11].

2.2. Classification and Assessment Technique

Light pollution, manifesting as wide-area pollution, holds the potential for extensive environmental degradation, characterized by its immediate impact [12]. Its repercussions on the surrounding environment exhibit variability contingent upon the location. Proximity to a direct light source may be overwhelming, while alternative scenarios may offer advantageous illumination. Within this discourse, the deleterious environmental consequences of light pollution in the proximate vicinity are denoted as local pollution. Whether in expansive or confined areas, light pollution manifests noteworthy adverse effects. Across broad expanses, the far-reaching propagation of light heightens its influence on astronomical research and the ecological milieu. In more confined regions, light pollution becomes intricately interwoven with economic and societal progress, alongside advances in lighting technology. The International Dark Sky Association (IDA) classifies sky glow as a form of wide-area pollution, while glare, light intrusion, and stray light are regarded as manifestations of local pollution [13]. Irrespective of the classification of light pollution, the spectral irradiance received at the human eye’s level serves as a primary metric for assessing the degree of human exposure to artificial light at night and its subsequent health impacts [14]. The exploration of data testing methods, equipment, collection indicators, accuracy, and the consideration of lunar phase, meteorology, and other variables contribute fundamentally to the evaluation of the light environment [15,16].

2.2.1. Wide-Area Light Pollution Assessment Technique

Sky glow, the phenomenon illuminating the nocturnal sky, detrimentally impacts astronomical observation and research, constituting the inaugural recognition of light pollution [16]. Turnrose et al. [17] quantified light pollution and formulated a simulation model for calculating its manifestation in the night sky. This mathematical model, pivotal in light pollution studies, originally focused on solving sky luminance, subsequently evolving to encompass diverse perspectives and furnish comprehensive assessments. Aubé et al. [18] conducted a comparative analysis between the MSNsRAu and ILLUMINA models. The MSNsRAu model, rooted in the concept of single scattering, demonstrates computational efficiency and accuracy in experiments involving an extensive array of grid points and diverse light spectra or lamp distributions. In contrast, the ILLUMINA model attains high accuracy under various turbidity conditions but is computationally time-intensive due to its second-order scattering calculation. These two models complement each other, with one emphasizing monitoring and research and the other adapting regional resolutions based on testing requirements. Refer to Table 2 for additional insights into the mathematical models of light pollution [16,19,20,21,22,23].
The confluence of satellite imagery and the World Atlas of Artificial Night Sky Brightness has precipitated the rapid development of large-scale regional modeling of ground–air light pollution based on the sky atlas, significantly enhancing our comprehension of this phenomenon [24]. The atlas’s revelations identified Italy and South Korea as the most light-polluted nations among the G20, while Australia exhibited the least pollution. A staggering 83% of the global population resided in areas impacted by artificial lighting, with the highest intensity of light pollution concentrated in densely populated urban centers [25]. Research in Europe has indicated the expansion of urban light pollution. Despite localized decreases in light pollution intensity within city centers, attributed to economic factors, an overarching trend of intensification persists [24,26]. Images, as direct reflections of light pollution levels, constitute a pivotal method for assessing light pollution on a broader scale. These images, obtainable through various means such as satellite remote sensing and aerial imagery, vary in range and accuracy, contingent upon factors like photo pixel resolution, amalgamated test results of ground light pollution, and the constructed relationship model between them. External variables, including weather, lunar phase, and air quality, also influence the acquisition of pertinent data. For further insights into image analysis of light pollution, refer to Table 3 [27,28,29].
The precise assessment of light pollution necessitates accurate measurement, a task facilitated by the use of sophisticated equipment for collecting quantitative data. The choice of equipment should align with the specific objectives of the measurement. For example, the sky quality meter (SQM) is a commonly employed tool for measuring luminance in dark skies within urban areas [30]. Alamús et al. [31] employed a hyperspectral imager to identify key indicators of light pollution, measuring levels in downtown Barcelona, including ground spectral radiation in the city’s nocturnal environment. Bettanini et al. [32] introduced a flight test device equipped on an autonomous payload, utilizing stratospheric probe balloons to measure sky brightness and ground light pollution. This device, incorporating commercially available components, including image acquisition, can be adapted for use with drones, stratospheric balloons, and tethered balloons, as illustrated in Figure 1 [24]. By amalgamating ground and sky observations with satellite imagery, the device adeptly generated a comprehensive map of ground source emissions. For more detailed insights into the quantitative observation of light pollution, refer to Table 4 [24,33,34,35,36].
Within methodologies for assessing light pollution, the formulation of a model that establishes the relationship between images and measurement results assumes paramount significance. Duriscoe et al. [37] discerned the distance relationship between sky brightness and the observer’s position concerning the upward radiation source, proposing a straightforward spatial model. They crafted a radiation transmission model demonstrating a robust correlation between observed and predicted data. Kolláth et al. [26] amalgamated information from satellite and ground measurements to authenticate the simulation’s efficacy and validate the model’s scientific underpinnings. In a subsequent work, Kolláth et al. [25] introduced a measurement system for assessing light pollution grounded in the “Advanced Cerro Paranal Sky Model”. This system captures the spectral characteristics of urban lighting devices, aligning them with satellite-captured image data to facilitate a comprehensive evaluation of the light environment and light pollution control. However, it is imperative to note that this system necessitates extensive environmental testing, and its applicability in intricate settings warrants further validation.

2.2.2. Local-Area Light Pollution Assessment Technique

Local-area light pollution encompasses challenges such as light intrusion and glare, carrying substantial implications for traffic safety, physical health, and energy consumption. In a comprehensive analysis of global light pollution’s economic dimensions, Gallaway et al. [2] utilized unique remote sensing and economic data from the World Bank. Their findings illuminated parallels between light pollution and other forms of pollution, identifying population and GDP as pivotal explanatory variables. Czarnecka et al. [38] identified the quantity of light sources in a given area as the primary factor influencing light pollution. The intensity of its impact hinges on factors such as lighting design, types of lamps employed, and the implementation of preventive measures. Descriptive data, including color temperature, peak wavelength, main wavelength, and photoreceptor stimulation value, play a pivotal role in characterizing local influences.
Quek et al. [12] undertook a comparative analysis, categorizing the suitability of brightness levels and dim scenarios. Hybrid models like DGP and Ecologist demonstrated a high correlation in both regions, surpassing metrics reliant solely on one effect [39]. Despite employing composite indicators to assess the optical environment of survey scenes, their applicability in complex lighting environments necessitates further validation.

2.3. Techniques for Light Pollution Control on Policy Formulation

In the domain of light pollution control and prevention techniques, policies and methodologies evolve from an understanding of light pollution and technological advancements. Progressive experiments consistently demonstrate the efficacy of light pollution control measures. Green et al. [40] emphasize that cities of comparable populations, but with established light pollution policies and proactive control measures, manifest markedly lower light monitoring indexes, as depicted in Figure 2.
Light pollution, deemed a form of energy pollution, distinguishes itself from other energy pollutants such as noise, vibration, and radiation due to its extensive impact. Scholars have persistently deliberated on prevention and control strategies for light pollution. In addition to the spatial assessment of light pollution discussed earlier, a two-dimensional evaluation in the comprehensive space–time dimension, coupled with management and prevention approaches akin to energy pollutants like noise, has proven influential in guiding policy formulation. Votsi et al. [14] introduced a classification control system for manned areas, unmanned areas, areas requiring lighting, and areas without lighting. This approach considers both the impact of light pollution on people and the ecological ramifications in unpopulated regions. They advocate for governmental adoption of the “red line” (indicating the limit of optical environment quality) as the macro-management target for the optical environment at the national or regional level. Zheng et al. [41] conducted long-term monitoring and evaluation of light pollution in Africa using sensor data from 1992 to 2018. Results indicated that the relationship between external human activities and light pollution within protected areas becomes invalid if the buffer distance exceeds 245 km.

3. Legislation and Standards on Light Pollution

Technological advancements have significantly enhanced our comprehension of light pollution, offering valuable guidance for regulators [16]. Measurement techniques play a pivotal role in both understanding light pollution and devising effective policy interventions. The data obtained through technological means establishes the bedrock for evidence-based policy-making [19]. As a result, government intervention assumes a central role in effectively preventing and mitigating light pollution.
Diverse strategies have emerged to address light pollution. One approach involves regulating the quality of lighting sources, encompassing source control to manage the brightness and luminous intensity of lighting fixtures [20]. Another strategy entails the implementation of specialized legislation dedicated to light pollution management [42]. A third strategy integrates light pollution considerations with local urban characteristics, such as starry sky preservation, military bases, and scientific research [1].
Additionally, the establishment of local protection areas, such as dark sky parks and restrictions on artificial lighting in natural reserves, constitutes a fourth strategy [43]. These initiatives aim to preserve the natural dark sky by implementing appropriate lighting regulations. While specific implementation processes may exhibit gaps in alignment with ongoing light pollution research, the overarching concept amalgamates considerations for wide-area (large-scale) and local-area (lighting source) perspectives. This consensus fosters a unified approach to classification control and legislation.

3.1. National Legislation

Divergent approaches to light pollution management exist among different states, notably comprehensive legislation and special legislation. Numerous countries have instituted national or regional laws and regulations tailored to address light pollution based on their unique circumstances. Notable examples include the Czech Republic, Great Britain, and France, each adopting distinct legislative frameworks.
France distinguishes itself as a country with comprehensive light pollution management legislation. In 2010, the French Environmental Code incorporated specific elements directed at preventing light pollution [44]. Subsequently, France implemented the Decree on the Prevention and Restriction of Light Pollution, introducing limits for lighting signs and advertising. The Ministry of Ecology and Inclusive Transformation further enacted the Law on the Prevention, Reduction, and Restriction of Light Pollution to combat the excessive impact of light pollution on humans, animals, plants, ecosystems, energy consumption, and night sky observations [19]. Additional details regarding some of the laws and policies in France are available in Table 5.
In 2007, Slovenia demonstrated its commitment to safeguarding the night sky from light pollution by implementing the world’s first national light pollution prevention bill [28]. According to this legislation, all lighting equipment must be equipped with lampshades, serving a dual purpose. Firstly, it intercepts and curbs the uncontrolled spread of light into the sky, thereby preserving the visibility of stars. Secondly, it concentrates the light within a specified range, significantly reducing energy waste [21].
South Korea has undertaken significant measures through special legislation and the establishment of relevant standards and regulations. In January 2012, South Korea established the DDP Light Environment Agreement to enhance the light environment around Seoul’s Dongdaemun Design Plaza. This agreement, a crucial step in South Korea’s light environment policy management, encompassed ten principles for improvement [4]. In 2013, South Korea enacted the Law on the Prevention and Control of Light Pollution by Artificial Lighting, with subsequent revisions in 2017 and 2020. This law delineates the responsibilities of the state, local governments, and citizens. The state formulates comprehensive policies, local governments implement prevention and control measures, and the public actively participates in light pollution prevention and control efforts. The legislation focuses primarily on behavior restrictions and fines, imposing stringent measures for nighttime lighting and light pollution. Local authorities define the location, brightness, and operating hours of major lighting installations. Macro-management involves the development and implementation of light pollution prevention plans by local governments, encompassing zoning management of the light environment based on the region’s ecological value and national objectives. The law also establishes light radiation tolerance standards [41].
South Korea has implemented supporting policies and regulations, such as the Comprehensive Plan for Light Pollution Prevention and Control (2014–2018) and the Comprehensive Plan for Light Pollution Prevention and Control (2019–2023). These plans mandate the annual release of performance evaluation results for municipal and provincial light pollution prevention and control projects.
To ensure effective enforcement, South Korea places great importance on formulating supporting rules and regulations, including the Light Pollution Inspection Standards and the Artificial Lighting Implementation Rules for the Prevention of Light Pollution (Ministry of Environment Order No. 864) [45]. There are also recommendations for street lamp installation management to prevent light pollution (Environment Announcement No. 2021-169), guidelines for the installation and management of safety lamps and park lamps to prevent light pollution (Ministry of Environment Announcement No. 2021-170), recommendations for managing advertising lighting installations to prevent light pollution (Ministry of Environment Announcement No. 2021-171), recommendations for managing decoration lamp installations to prevent light pollution (Environment Announcement No. 202-172), and regulations governing the operation of the light pollution prevention committee (Ministry of Environment Order No. 1520).

3.2. Local Legislation

Italy has adopted a regional approach to crafting laws and regulations for light pollution prevention and control. Currently, 15 regions in Italy, including Lombardy, Emilia-Romagna, Marche, Lazio, Campania, and Veneto, have implemented laws specifically targeting light pollution prevention within their respective territories. These laws cover over two-thirds of Italy’s population and major cities such as Milan, Rome, Venice, Florence, Bologna, and Naples. Italy places particular emphasis on employing different lighting standards for various buildings, especially classical structures. In historic districts filled with ancient buildings, strict limitations are imposed on the use of luminous advertisements. Instead, there is encouragement to utilize low-brightness, low-height, and miniaturized luminous advertisements. Detailed regulations are established to govern different types of decorative lighting for buildings [46].
In the United States, there is no uniform national legislation specifically addressing light pollution. However, many states and cities have enacted numerous regulations based on their unique characteristics. Presently, at least 19 states, along with the District of Columbia and Puerto Rico, have implemented laws aimed at reducing light pollution [47]. Examples of these include Utah’s Light Pollution Prevention Law, Indiana’s Outdoor Lighting Pollution Prevention Act, Michigan’s Outdoor Lighting Act, New Mexico’s Night Sky Protection Act, Connecticut’s “The Night and the Sky Law,” and Arkansas’s Night Sky Protection Act. Some states, like New Hampshire, prioritize the preservation of dark skies as a rural feature, while coastal areas are concerned about the impact of lighting on birds and marine life. In Florida, state-level lighting regulations (such as Florida Bureau of Statistics Section 161.163 and Florida Administrative Code 62B.55.001) provide guidance to local governments in protecting turtle hatching [37].
Local legislation regarding light pollution generally aligns with national standards or international lighting regulations. The specific content of such legislation varies depending on the objectives, often focusing on promoting energy conservation, ensuring public safety, enhancing aesthetic interests, and facilitating astronomical research. From a management perspective, these laws control nighttime construction activities, regulate outdoor lighting installations on public roads, and aim to preserve dark skies.

3.3. Standards

Several international or regional organizations have implemented restrictions on light pollution and established technical standards for a conducive lighting environment, procurement standards, etc. (Refer to Table 6). These standards serve as a valuable reference for curbing light pollution in diverse regions worldwide. For instance, the CIE 150 technical guidance provided by the International Lighting Committee emphasizes the establishment of different indicators for lighting based on time and varying environmental brightness areas, with specific limits defined [6]. A model lighting regulation, collaboratively developed by the Dark Sky Association and the North American Lighting Engineering Association, advocates for the creation of standardized and uniform lighting requirements tailored to the specific lighting needs of distinct areas [13].
While international organizations have issued the relevant recommendation standards, it is crucial to acknowledge that these standards may not be universally applicable due to variations in lighting product usage, climate, local customs, and economic development. Therefore, localized restriction standards for light pollution are essential to effectively promote the management process. Some countries have embraced this approach and developed localized standards. For example, Italy has three technical standards (UNI10819, UNI10439, and UNI9316) directly or indirectly related to light pollution prevention and control [22]. These standards prohibit excessive lighting and regulate the direction and brightness of lighting devices, thereby reducing light pollution.
Japan, recognizing the dangers of light pollution early on, affirmed the concept of light pollution in the Basic Environmental Plan issued in 1994. In 1998, the Japanese Environment Ministry published the Light Disaster Countermeasures Guidelines and revised them twice, in 2006 and 2021, aligning them with the CIE Guidelines. These guidelines uniformly divide the light environment across the country, except for Zone E0, which is not divided [52]. The Japanese guidelines primarily focus on four aspects: light distribution, optical communication ratio, brightness, and color temperature. They reference CIE150:2003 for light distribution, CIE150:2017 for vertical illumination, brightness, and corresponding limits, and the Japanese JIS Z 9127 (2020) for sports glare value. The light values for roads, squares, and parks are based on JIS Z 9110 (2010) standards, with the evaluation method referencing CIE112:1994. The glare index for outdoor pedestrians is based on JIEG-011 (2018), and lighting indicators follow JIES-010 (2014). The color temperature level of lighting fixtures is described according to the Japanese JIS Z 9112 standard. In accordance with the blue light standard issued by the IDA in 2014, the recommended color temperature for lighting fixtures should be below 3000K [53]. Furthermore, Japan also incorporates requirements from the Regional Lighting Environment Planning Manual (2000) and the Light Pollution Prevention System Guidelines (2001) to prevent light pollution.

4. Discussions

Multidisciplinary research plays a pivotal role in the prevention and control of light pollution. The utilization of evaluation technology is indispensable for formulating effective policies in this area. Furthermore, the formulation and implementation of environmental management policies are crucial for achieving successful pollution prevention and control outcomes. In the current global context of carbon reduction, promoting the rational use of lighting technology and carefully selecting wide-area and local light pollution monitoring indicators are imperative. Establishing a standardized and comparable light pollution monitoring technology system is of utmost importance to ensure the effectiveness of light pollution prevention efforts. Strategies such as “ambient luminance partition”, “purchasing suitable lighting products”, and “special area protection” have emerged as key methods to mitigate light pollution [15]. These approaches are increasingly being adopted by various regions due to their positive social benefits, alignment with the imbalanced nature of global economic development, and practicality in implementation.

4.1. Key Methods

4.1.1. Environmental Brightness Partition

Table 7 outlines the light pollution control requirements established by international organizations. According to these partition standards, the installation of light sources with varying performance indicators is permitted in the corresponding areas. Control requirements vary between pre- and post-lights-out periods to accommodate people’s daily work and rest routines, with post-lights-out regulations generally being more stringent. Environmental brightness is typically divided into 4–5 types of areas, covering aspects such as sky glow, lamps, light intrusion, advertising, and building facade brightness. Different light pollution monitoring indicators are employed, and recommended emission limits are set for different ambient brightness areas.
Light environment zoning management is embraced by many countries, regardless of the existence of specific legislation on light pollution. For instance, South Korea has legally categorized the light environment into four types for management purposes, and Japan has issued the Light Pollution Prevention and Control Guidelines [53]. The Japanese guidelines underscore the importance of tailoring light environment management to regional characteristics, such as social conditions, environmental richness, and star observation. It suggests that different light environment types should be designated based on local resources, allowing city-, town-, and village-level public groups to determine the applicable level of light environment within their jurisdiction. The light environment partition is based on CIE150 recommendations.
In the United States, light pollution control measures are formulated by individual states in accordance with their economic conditions and development strategies. Each state determines the ambient brightness levels for outdoor environments based on local conditions. Relative ambient lighting levels and state-wide default areas are specified for each illuminated area. Local jurisdictions have the flexibility to adjust the range of applicable brightness areas (LZ4) and expand or reduce the scope of brightness areas falling within the state’s designated LZ1, LZ2, and LZ3, as shown in Table 8.

4.1.2. Lighting Product Control

In countries lacking specific legislation on light pollution, efforts to prevent it often rely on guidance from international lighting organizations such as the European Standardization Committee, International Lighting Committee, Society of Lighting Engineering, and Association of Lighting Professionals. These organizations provide measures and recommendations for controlling light pollution [7]. Additionally, in certain regions, local procurement standards for lighting products have been established to regulate the spread of light pollution.
An example of such standards is the revised EU Green Public Procurement Standards for Road Lighting and Traffic Signals [54] (GPP), which introduced new technology procurement criteria to address light pollution. The GPP focuses on two main categories of light pollution: TS8, annoyance, and TS9, ecological light pollution and star visibility. TS8 specifies that residential lighting should have color temperatures below 3000 K to minimize the perceived impact of light that is considered “abrupt”. The dimming or switching off of lights must be implemented according to the purchaser’s specifications. TS9 recommends that the lamp’s G index should be no less than 1.5 and at least 2.0 in ecologically sensitive areas near observatories. The GPP also suggests the implementation of dimming or shutdown schedules to limit total nighttime light emission in ecologically sensitive areas. Many aspects of the GPP align with the low-impact lighting standards promoted by Germany, Italy, Slovenia, and other countries.
These measures and standards provide guidelines for the procurement and use of lighting products to minimize light pollution. By incorporating criteria such as color temperature, dimming capabilities, and ecological considerations, these standards aim to ensure that lighting installations are designed and implemented in a manner that mitigates their impact on the environment and human perception.

4.1.3. Dark Sky Protection Area

The International Dark Sky Association (IDA) launched the “Dark Night Reserve Certification” program in 2001, comprising five distinct designations for areas committed to dark sky protection [9]. These designations are as follows:
  • International Dark Sky Communities: These are legally organized cities and towns that have implemented outdoor lighting ordinances and educational efforts to raise awareness about the importance of dark skies.
  • International Dark Sky Parks: These are publicly or privately owned spaces, primarily dedicated to natural conservation, that have implemented responsible outdoor lighting practices and offer dark sky programs for visitors.
  • International Dark Sky Reserves: Reserves consist of a core area with significant darkness surrounded by a populated periphery. Policy controls are enacted in the periphery to protect the darkness of the core.
  • International Dark Sky Sanctuaries: Sanctuaries are typically remote and exceptionally dark locations that have fragile conservation states and require special protection.
  • Urban Night Sky Places: These are sites located near or within large urban areas that actively promote an authentic nighttime experience despite significant artificial light. These places may not qualify for designation in other dark sky categories.
In regions blessed with abundant sky resources or a commitment to controlling light pollution, it is advisable to establish dark sky areas in accordance with the International Dark Sky Association (IDA) certification standards. For instance, the state of New Hampshire in the United States has prioritized the preservation of dark skies as a rural feature, urging municipalities to enact ordinances and regulations to minimize light pollution and conserve energy [55]. Presently, the global landscape includes 34 dark sky communities, 112 dark sky parks, 19 dark sky reserves, 15 dark core areas, 5 urban dark areas (all in the United States), and 6 night expansion areas, as illustrated in Figure 3 and Figure 4.
It is worth noting that the IDA also acknowledged Dark Sky Friendly Developments of Distinction (retired in 2020). This category encompassed subdivisions, master-planned communities, and unincorporated neighborhoods and townships actively promoting a more natural night sky, even if they did not meet the criteria for the International Dark Sky Community designation.
These dark sky reserves are distributed across various countries and regions in Europe, America, and Asia, playing a crucial role in mitigating the negative impacts of light pollution on biodiversity and scientific research. In certain countries or regions, observatories have been designated as dark areas to safeguard the astronomical quality of institutions. For instance, Spain has enacted special laws to protect the astronomical observations of the Institute of Astrophysics in the Canary Islands [57].

4.2. The Integration of Evaluation Technique and Policy

Although there are various research methods for the assessment of light pollution, the primary focus is on accurately obtaining ground light pollution data under cloudless and low atmospheric aerosol conditions and establishing a radiation transmission model that correlates well with the measured values. However, there is a lack of studies on the consistency of results between different evaluation methods, which hinders the effective application of excellent evaluation methods in policy-making. Therefore, it is essential to establish a set of general light pollution assessment methods and develop quantitative value conversion methods among different approaches to enhance the combination between measurement technology and policy for reducing light pollution. Importantly, legislation without a sufficient understanding of light pollution can hinder the development of lighting technology. Furthermore, there is a growing concern about the effectiveness of prevention, making the mitigation of negative consequences part of the public agenda in many countries worldwide [58].
The CIE 150 (2017) standard can serve as a reference for the compilation of national light pollution codes [6]. However, it is important to consider regional differences when implementing the code. While the code is generally applicable to most countries engaged in light pollution prevention and management, individual nations should tailor their measures based on their national conditions to facilitate the promotion of national policies. Common ideas for light pollution control include adopting ambient brightness partitioning or similar modes for light environment management or light pollution control, implementing source control of lighting products, and designating and protecting areas with special requirements for dark environments [27].
Based on the literature review conducted, it is evident that technology development facilitates the formulation of light pollution policies. While policy-making represents the highest level of work, technology serves as the foundation. Policies can drive technological development, and technology can improve policy formulation. However, technology improvements often take longer than policy formulation. Therefore, once the basic light pollution policy is formulated, it can accelerate the technical research work in the field of light pollution prevention and control. Thus, for environmental managers, two main approaches can be employed to establish strategies and reduce light pollution:
  • Formulating related policies through legislation in a top-down approach [59]. Two common ways of legislating light pollution have been studied, as discussed by Morgan-Taylor et. al. [60]. The first approach involves enacting special legislation specifically aimed at addressing light pollution, which has been shown to be more effective in pollution prevention and control [61]. This method includes the development of specific laws and regulations, such as the Light Pollution Prevention and Control Law in Korea, which has been accompanied by supporting standards like the Light Pollution Detection Standards [45]. On the other hand, the second approach is “bolt-on” legislation, which extends existing laws to include light pollution regulations. However, “bolt-on” legislation often results in incomplete definitions and restrictions. For instance, in some cases, light pollution is defined as “the artificial light emitted from the workplace with adverse health or harmful substances,” while ignoring the impact on the glow of the sky [62];
  • Setting technical standards. These standards encompass various aspects, including restrictions based on emission intensity and the influence of light sources [27]. For example, parameters related to brightness and illumination limits can be established based on the strength of the CIE 150 standard. Additionally, specific standards can be developed to regulate lighting products and their impact on light pollution [63]. Furthermore, time restrictions can be implemented for the operation of lights [64]. For instance, specific lighting schedules can be set for commercial advertisements, and the lighting duration in public areas can be adjusted based on the season and sunset. In some countries, such as France, legislation has adopted a curfew approach that not only addresses the reduction of sky glow and light trespass but also focuses on energy conservation [65]. For example, all room lights must be turned off within an hour after the last person leaves, and outdoor lighting in commercial and non-residential buildings must be switched off after 7 A.M. Similarly, in certain cities in China, commercial advertising is required to be turned off after 21:00 to mitigate light pollution.

5. Conclusions

The insufficient understanding of light pollution has led to imperfect policies and reduced effectiveness in its prevention. Therefore, there is a need to review the characteristics of light pollution, including the assessment technique, policy, and legislation. Through the review, the following can be concluded:
  • Technical standards are required to prevent light pollution. Examples from countries like South Korea, France, Japan, and several European nations provide insights for other countries when formulating their own policies. For example, light pollution was decreased by 6% in France through the legislation of artificial light.
  • Key approaches are suggested for global light pollution control, including implementing ambient brightness zoning, regulating lighting product usage, and establishing dark sky reserves. These methods are recommended for areas where immediate policy formulation might not be feasible.
  • Technology and policy should be integrated: The mutual promotion between technology and policy-making is identified as a significant trend in future research. The precise data coming from satellite imagery, drones, and balloons, could provide guidance when making the policies.

Author Contributions

Conceptualization, Y.H. and P.W.; investigation, Z.X. and Z.Z.; resources, Z.X. and D.J.; writing—original draft preparation, Y.H.; writing—review and editing, Y.H. and D.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Ecological Environment Standard Project of China (No. 2022-2), National Natural Science Foundation of China (Nos. 51806151; 51776140), and Innovation Team, College and University Municipality of Tianjin (No. TD13-5088).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy restrictions.

Acknowledgments

The authors would like to express many thanks to all the anonymous reviewers.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Cao, M.; Xu, T.; Yin, D. Understanding light pollution: Recent advances on its health threats and regulations. J. Environ. Sci. 2023, 127, 589–602. [Google Scholar] [CrossRef] [PubMed]
  2. Gallaway, T.; Olsen, R.N.; Mitchell, D.M. The economics of global light pollution. Ecol. Econ. 2010, 69, 658–665. [Google Scholar] [CrossRef]
  3. Falchi, F. Campaign of sky brightness and extinction measurements using a portable CCD camera. Mon. Not. R. Astron. Soc. 2011, 412, 33–48. [Google Scholar] [CrossRef]
  4. Sung, C.Y. Light pollution as an ecological edge effect: Landscape ecological analysis of light pollution in protected areas in Korea. J. Nat. Conserv. 2022, 66, 126148. [Google Scholar] [CrossRef]
  5. Model Lighting Ordinance. Available online: https://darksky.org/resources/guides-and-how-tos/model-lighting-ordinances/ (accessed on 30 May 2024).
  6. Light Pollution. Available online: http://cie.co.at/eilvterm/17-29-177 (accessed on 10 December 2023).
  7. Longcore, T.; Rich, C. Ecological light pollution. Front. Ecol. Environ. 2004, 2, 191–198. [Google Scholar] [CrossRef]
  8. Narisada, K.; Schreuder, D. Light Pollution Handbook, 1st ed.; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2013; pp. 61–77. [Google Scholar] [CrossRef]
  9. Light Pollution. Available online: http://www.darksky.org/light-pollution/ (accessed on 10 December 2023).
  10. Guidelines on Minimizing Sky Glow. Available online: https://cie.co.at/publications/guidelines-minimizing-sky-glow (accessed on 10 December 2023).
  11. Outdoor Work Places. Available online: https://www.iso.org/standard/76342.html (accessed on 10 December 2023).
  12. Quek, G.; Wienold, J.; Khanie, M.S.; Erell, E.; Kaftan, E.; Tzemepelikos, A.; Konstantzos, I.; Christofferen, J.; Kuhn, T.; Andersen, M. Comparing performance of discomfort glare metrics in high and low adaptation levels. Build. Environ. 2021, 206, 108335. [Google Scholar] [CrossRef]
  13. Riza, L.S.; Izzuddin, A.; Utama, J.A.; Samah, K.A.F.A.; Herdiwijaya, D.; Hidayat, T.; Anugraha, R.; Mumpuni, E.S. Data analysis techniques in light pollution: A survey and taxonomy. New Astron. Rev. 2022, 95, 101663. [Google Scholar] [CrossRef]
  14. Votsi, N.P.; Kallimanis, A.S.; Pantis, I.D. An environmental index of noise and light pollution at EU by spatial correlation of quiet and unlit areas. Environ. Pollut. 2017, 221, 459–469. [Google Scholar] [CrossRef]
  15. Mander, S.; Alam, F.; Lovreglio, R.; Ooi, M. How to measure light pollution—A systematic review of methods and applications. Sustain. Cities Soc. 2023, 92, 104465. [Google Scholar] [CrossRef]
  16. Walker, M.F. Light pollution in California and Arizona. Publ. Astron. Soc. Pac. 1973, 85, 507–508. [Google Scholar] [CrossRef]
  17. Turnrose, B.E. Absolute spectral energy distribution of the night sky at Palomar and Mount Wilson observatories. Publ. Astron. Soc. Pac. 1974, 86, 545–551. [Google Scholar] [CrossRef]
  18. Aubé, M.; Kocifaj, M. Using two light-pollution models to investigate artificial sky radiances at Canary Islands observatories. Mon. Not. R. Astron. Soc. 2012, 422, 819–830. [Google Scholar] [CrossRef]
  19. Pike, R. A simple computer model for the growth of light pollution. J. RASC 1976, 70, 116–126. [Google Scholar]
  20. Garstang, R.H. Night sky brightness at observatories and sites. Publ. Astron. Soc. Pac. 1989, 101, 306–329. [Google Scholar] [CrossRef]
  21. Garstang, R.H. Dust and light pollution. Publ. Astron. Soc. Pac. 1991, 103, 1109–1116. [Google Scholar] [CrossRef]
  22. Puschnig, J.; Schwope, A.; Posch, T.; Schwarz, R. The night sky brightness at Potsdam-Babelsberg. J. Quant. Spectrosc. Radiat. Transf. 2014, 139, 76–81. [Google Scholar] [CrossRef]
  23. Cinzano, P.; Falchi, F. Quantifying light pollution. J. Quant. Spectrosc. Radiat. Transf. 2014, 139, 13–20. [Google Scholar] [CrossRef]
  24. Falchi, F.; Cinzano, P.; Duriscoe, D.; Kyba, C.C.M.; Elvidge, C.D.; Baugh, K.; Portnov, B.A.; Rybnikova, N.A.; Furgoni, R. The new world atlas of artificial night sky brightness. Sci. Adv. 2016, 2, e1600377. [Google Scholar] [CrossRef] [PubMed]
  25. Kolláth, Z.; Száz, D.; Kolláth, K. Measurements and modelling of artificial sky brightness: Combining remote sensing from satellites and ground-based observations. Remote Sens. 2021, 13, 3653. [Google Scholar] [CrossRef]
  26. Kolláth, Z.; Cool, A.; Jechow, A.; Kolláth, K.; Száz, D.; Tong, K.P. Introducing the dark sky unit for multi-spectral measurement of the night sky quality with commercial digital cameras. J. Quant. Spectrosc. Radiat. Transf. 2020, 253, 107162. [Google Scholar] [CrossRef]
  27. Chalkias, C.; Petrakis, M.C.; Psiloglou, B.E.; Lianou, M. Modelling of light pollution in suburban areas using remotely sensed imagery and GIS. J. Environ. 2006, 79, 57–63. [Google Scholar] [CrossRef] [PubMed]
  28. Falchi, F.; Cinzano, P.; Elvidge, C.D.; Keith, D.M.; Haim, A. Limiting the impact of light pollution on human health, environment and stellar visibility. J. Environ. Manag. 2011, 92, 2714–2722. [Google Scholar] [CrossRef] [PubMed]
  29. Elvidge, C.D.; Baugh, K.E.; Zhizhin, M.N.; Hsu, F. Why VIIRS data are superior to DMSP for mapping nighttime lights. Proc. Asia-Pac. Adv. Netw. 2013, 35, 62–69. [Google Scholar] [CrossRef]
  30. Puschnig, J.; Wallner, S.; Posch, T. Circalunar variations of the night sky brightness-an FFT perspective on the impact of light pollution. Mon. Not. R. Astron. Soc. 2020, 492, 2622–2637. [Google Scholar] [CrossRef]
  31. Alamús, R.; Bará, S.; Corbera, J.; Escofet, J.; Palà, V.; Pipia, L.; Tardà, A. Ground-based hyperspectral analysis of the urban nightscape. ISPRS J. Photogramm. Remote Sens. 2017, 124, 16–26. [Google Scholar] [CrossRef]
  32. Bettanini, C.; Bartolomei, M.; Aboudan, A.; Colombatti, G.; Olivieri, L. Flight test of an autonomous payload for measuring sky brightness and ground light pollution using a stratospheric sounding balloon. Acta Astronaut. 2022, 191, 11–21. [Google Scholar] [CrossRef]
  33. Duriscoe, D.M.; Luginbuhl, C.B.; Moore, C.A. Measuring night-sky brightness with a wide-field CCD camera. Publ. Astron. Soc. Pac. 2007, 119, 192–214. [Google Scholar] [CrossRef]
  34. Shen, T.X.; Wang, L.X.; Han, X.Q. Measure and study on the lighting environment of road tunnel by SM lighting measuring system. Light Light. 2010, 34, 5–8. [Google Scholar]
  35. Aceituno, J.; Sanchez, S.F.; Aceituno, F.J.; Enríquez, D.G.; Negro, J.J.; Soriguer, R.C.; Gómez, G.S. An all-sky transmission monitor: ASTMON. Publ. Astron. Soc. Pac. 2011, 123, 1076–1086. [Google Scholar] [CrossRef]
  36. Spoelstra, H. New device for monitoring the colors of the night. J. Quant. Spectrosc. Radiat. Transf. 2014, 139, 82–89. [Google Scholar] [CrossRef]
  37. Duriscoe, D.M.; Anderson, S.J.; Luginbuhl, C.B.; Baugh, K.E. A simplified model of all-sky artificial sky glow derived from VIIRS Day/Night band data. J. Quant. Spectrosc. Radiat. Transf. 2018, 214, 133–145. [Google Scholar] [CrossRef]
  38. Czarnecka, K.; Błażejczyk, K.; Morita, T. Characteristics of light pollution–A case study of Warsaw (Poland) and Fukuoka (Japan). Environ. Pollut. 2021, 291, 118113. [Google Scholar] [CrossRef] [PubMed]
  39. Lopez-Farias, R.; Valdez, S.I.; Paredes-Tavares, J.; Lamphar, H. Optimization of sensor locations for a light pollution monitoring network. J. Quant. Spectrosc. Radiat. Transf. 2023, 304, 108584. [Google Scholar] [CrossRef]
  40. Green, R.F.; Luginbuhl, C.B.; Wainscoat, R.J.; Duriscoe, D. The growing threat of light pollution to ground-based observatories. Astron. Astrophys. 2022, 30, 1–49. [Google Scholar] [CrossRef]
  41. Zheng, Z.; Wu, Z.; Chen, Y.; Guo, G.; Cao, Z.; Yang, Z.W.; Marinello, F. Africa’s protected areas are brightening at night: A long-term light pollution monitor based on nighttime light imagery. Glob. Environ. Chang. 2021, 69, 102318. [Google Scholar] [CrossRef]
  42. Noll, S.; Kausch, W.; Barden, M.; Jones, A.M.; Szyszka, A.; Kimeswenger, S.; Vinther, J. An atmospheric radiation model for Cerro Paranal-I. The optical spectral range. Astron. Astrophys. 2012, 543, 1–23. [Google Scholar] [CrossRef]
  43. Nie, Y.W.; Lan, T.; Yu, M. Scenic sites selection in dark-sky park based on NPP/VIIRS: A case study in Fujian Province. Procedia Comput. 2019, 154, 798–805. [Google Scholar] [CrossRef]
  44. Aksaker, N.; Yerli, S.K.; Kurt, Z.; Bayazit, M.; Akcay, A.; Erdoğan, M.A. A case study of light pollution in France. Astrophys. Space Sci. 2020, 365, 1–9. [Google Scholar] [CrossRef]
  45. Ministry of Environment. Available online: http://me.go.kr/home/web/main.do (accessed on 10 December 2023).
  46. Zitelli, V.; Sora, M.D.; Ferrini, F. Local and national regulations on light pollution in Italy. In Symposium-International Astronomical Union; Cambridge University Press: Cambridge, UK, 2001; Volume 196, pp. 111–116. [Google Scholar] [CrossRef]
  47. States Shut Out Light Pollution. Available online: https://www.ncsl.org/environment-and-natural-resources/states-shut-out-light-pollution (accessed on 10 December 2023).
  48. Zielinska-Dabkowska, K.M.; Xavia, K. Global Approaches to Reduce Light Pollution from Media Architecture and Non-Static, Self-Luminous LED Displays for Mixed-Use Urban Developments. Sustainability 2019, 11, 3446. [Google Scholar] [CrossRef]
  49. EN12464-2:2014; Light and Lighting-Lighting of Work Places—Part 2: Outdoor Workplaces. European Committee for Standardization: Brussels, Belgium, 2014.
  50. CIE 150: 2017; Guide on the Limitation of the Effects of Obtrusive Light from Outdoor Lighting Installations. 2nd ed. International Commission on Illumination: Vienna, Austria, 2017.
  51. ANSI/IES RP-39-19; Recommended Practice: Off-Roadway Sign Luminance. Illuminating Engineering Society: New York, NY, USA, 2019.
  52. The Light Pollution Prevention and Control Guidelines. Available online: https://www.env.go.jp/air/hikarigai-gaido-R3.pdf.pdf (accessed on 10 December 2023).
  53. Classification of Fluorescent Lamps and Light Emitting Diodes by Chromaticity and Colour Rendering Property. Available online: https://webdesk.jsa.or.jp/preview/pre_jis_z_09112_000_000_2019_e_ed10_ch.pdf (accessed on 10 December 2023).
  54. Buying Green! A Handbook on Green Public Procurement. Available online: https://ec.europa.eu/environment/gpp/buying_handbook_en.htm (accessed on 10 December 2023).
  55. Falchi, F.; Furgoni, R.; Gallaway, T.A.; Rybnikova, N.A.; Portnov, B.A.; Baugh, K.E.; Cinzano, P.; Elvidge, C.D. Light pollution in USA and Europe: The good, the bad and the ugly. J. Environ. Manag. 2019, 248, 109227. [Google Scholar] [CrossRef]
  56. Find a Dark Sky Place. Available online: https://www.darksky.org/our-work/conservation/idsp/finder/ (accessed on 26 May 2024).
  57. Search: New Hamp. Available online: https://www.darksky.org/?s=new+hamp (accessed on 10 December 2023).
  58. Kolláth, Z.; Dömény, J.; Kolláth, K.; Nagy, B. Qualifying lighting remodeling in a Hungarian city based on light pollution effects. J. Quant. Spectrosc. Radiat. Transf. 2016, 181, 46–51. [Google Scholar] [CrossRef]
  59. Ngarambe, J.; Kim, G. Sustainable lighting policies: The contribution of advertisement and decorative lighting to local light pollution in Seoul South Korea. Sustainability 2018, 10, 1007. [Google Scholar] [CrossRef]
  60. Morgan-Taylor, M.; Kim, J.T. Regulating Artificial Light at Night: A Comparison Between the South Korean and English Approaches. IJSL Int. J. Sustain. Light. 2016, 18, 21–31. [Google Scholar] [CrossRef]
  61. Zissis, G. Sustainable lighting and light pollution: A critical issue for the pre-sent generation, a challenge to the future. Sustainability 2020, 12, 4552. [Google Scholar] [CrossRef]
  62. The Statutory Nuisances (Miscellaneous Provisions) (Wales) Regulations 2007. Available online: http://www.legislation.gov.uk/wsi/2007/117/regulation/3/made (accessed on 10 December 2023).
  63. Schulte-Römer, N.; Meier, J.; Söding, M.; Dannemann, E. The LED paradox: How light pollution challenges experts to reconsider sustainable lighting. Sustainability 2019, 11, 6160. [Google Scholar] [CrossRef]
  64. Lyytimäki, J. Avoiding overly bright future: The systems intelligence perspective on the management of light pollution. Environ. Dev. 2015, 16, 4–14. [Google Scholar] [CrossRef]
  65. Kaushik, K.; Nair, S.; Ahamad, A. Studying light pollution as an emerging environmental concern in India. J. Urban Manag. 2022, 11, 392–405. [Google Scholar] [CrossRef]
Figure 1. MINLU in flight configuration as drone, stratospheric balloon and tethered balloon payload [24].
Figure 1. MINLU in flight configuration as drone, stratospheric balloon and tethered balloon payload [24].
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Figure 2. U.S. NPS all-sky image comparison of images taken 27 km outside of Flagstaff, AZ (upper) and 31 km outside of Cheyenne [40].
Figure 2. U.S. NPS all-sky image comparison of images taken 27 km outside of Flagstaff, AZ (upper) and 31 km outside of Cheyenne [40].
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Figure 3. Locations designated as part of the International Dark Sky Places Program [56].
Figure 3. Locations designated as part of the International Dark Sky Places Program [56].
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Figure 4. IDA-issued five dark night area types and distribution ratio [56,57].
Figure 4. IDA-issued five dark night area types and distribution ratio [56,57].
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Table 1. Maximum obstructive light permitted for exterior lighting installations [6,11].
Table 1. Maximum obstructive light permitted for exterior lighting installations [6,11].
Environmental Illumination ZoneLight on PropertiesLuminaire IntensityUpward Light RatioLuminance
Ev (lx)I (cd)RUL (%)Lb (cd/m2)Ls (cd/m2)
Pre CurfewPost CurfewPre CurfewPost Curfew Building FaçadeSign
E120250000050
E251750050055400
E310210,00010001510800
E425525,000250025251000
E1 represents the dark zone; E2 represents the low luminance zone; E3 represents the medium luminance zone; E4 represents the high luminance zone.
Table 2. Previous studies on mathematical models for light pollution [16,19,20,21,22,23].
Table 2. Previous studies on mathematical models for light pollution [16,19,20,21,22,23].
TimeAuthorsResearch ObjectsKey Findings
1970Walker et al. [16]BrightnessPropose night sky brightness and condition of observatory sites
1976Pike et al. [19]Brightness; PopulationEstablish model of brightness–population relations
1989Garstang et al. [20]Brightness; Different citiesEstablish model of brightness–population–ground reflectivity
1991Garstang et al. [21]Brightness; Atmosphere conditionModify previous model method
2013Puschnig et al. [22]Brightness; CloudTypical night sky brightness in Berlin and night sky change in lunar cycles
2014Cinzano et al. [23]Energy distribution of lightEstablish model of luminous flux and observation sites
Table 3. Past studies on the image analysis of light pollution [27,28,29].
Table 3. Past studies on the image analysis of light pollution [27,28,29].
TimeAuthorsResearch ObjectsKey Findings
2006Chalkias et al. [27]Sky glowsEstablish model of night sky brightness in urban areas
2011Falchi et al. [28]Night skyAnalyze characteristics of light pollution in night sky
2013Elvidge et al. [29]VIIRS imageObtain actual color temperature of lighting facilities in land
Table 4. Past studies on quantitative analysis of light pollution [24,33,34,35,36].
Table 4. Past studies on quantitative analysis of light pollution [24,33,34,35,36].
TimeAuthorsResearch ObjectsKey Findings
2007Duriscoe et al. [33]Zenith luminanceDiscuss broadband measurement of the complex and variable night-sky spectrum
2010Shen et al. [34]Zenith luminanceMeasure lighting environment in tunnel
2011Aceituno et al. [35]Sky; CloudPresent the All-Sky Transmission Monitor (ASTMON) and prove its availability
2014Spoelstra et al. [36]Sky brightness in different areasDevelop a low-cost multi-filter instrument
2016Falchi et al. [24]Zenith luminancePresent the world atlas of artificial sky luminance by using light pollution propagation software
Table 5. Policy and legislation on light pollution in France [44].
Table 5. Policy and legislation on light pollution in France [44].
Policy NamePolicy Content
Civil codePrevent light pollution by “Neighbor nuisance system”
Code de l’environmentRestrict damage harm caused by artificial light to people and the environment
French light pollution lawReduce light pollution from business offices and other non-residential buildings
The Grenelle 2 actDefine the rules about the use of outdoor lighting installations
Concerning the prevention, reduction, and limiting of light pollutionReduce excessive interference to persons, animals, plants, and ecosystems
Table 6. Existing luminance requirements based on current lighting standards and guidelines for mixed-use urban zones [48].
Table 6. Existing luminance requirements based on current lighting standards and guidelines for mixed-use urban zones [48].
Lighting Standard/GuidelinesYear PublishedEnvironmental ZoneLuminance at Night (cd/m2)Curfew Times
EN12464-2:2014 [49] called Light and Lighting—Lighting of Work Places, Part 2: Outdoor Work Places2014E425
(Building facade)
1000
(sign)
CIE 150: 2017 [50], the Guide on the Limitation of the Effects of Obstructive Light from Outdoor Lighting Installations2017E425
(Building facade)
1000
(sign)
ILP’s Professional Lighting Guide (PLG 05): The Brightness of Illuminated Advertisement2014E4600
(up to 10 m2 illuminated area)
300
(over 10 m2 illuminated area)
ANSI/IES RP-39-19 [51], Recommended Practice: Off-Roadway Sign Luminance2019LZ240no
IDA’s Guidance for Electronic Message Centers (EMCs)2019LZ240yes
Table 7. Light pollution control requirement by international organizations [53].
Table 7. Light pollution control requirement by international organizations [53].
International OrganizationNumber of Ambient Brightness PartitionsTime Control RequirementsControl IndicatorsFocus
Commission International de l’Eclairage5Before and after the curfewLuminance, brightness, light intensity, and light ratioLight and lanterns, advertising light, and acceptance surface
Model Lighting Ordinance5--Light intensity, upper light through ratio, glare G indexLuminescence of lamps and lanterns
Lighting Europe4Before and after the curfew; the curfew is recommended at 23:00Luminance, brightness, light intensity, and light ratioReducing the number of lamps, luminous or receptive surfaces of building facades and advertisements
Table 8. Revised lighting area characteristics and rules in USA local jurisdictions [53].
Table 8. Revised lighting area characteristics and rules in USA local jurisdictions [53].
ZoneZoning InstructionsState-Wide Default AreaDefault Region with Increased LikelihoodDefault Region with a Reduced Likelihood
LZ1Dark areaGovernment-designated parks, recreational areas, and wildlife conservation areas. Those that are fully contained within the higher lighting area may be considered by the local government as part of that lighting area.Government-designated parks, recreational areas, wildlife reserves, or parts thereof. If included in such regions, it can be designated as LZ2 or LZ3.Not applicable.
LZ2Low brightness areaRural areas as defined by the 2010 United States Census.Special areas within the default LZ2 area may be designated as LZ3 or LZ4. Examples include special commercial areas located in rural areas or areas with special safety considerations.Special areas and government-designated parks within the default LZ2 area may be designated as LZ1 by local jurisdictions to lower lighting standards; there is no size limit.
LZ3Medium brightness areaUrban areas as defined in the 2010 US Census.Special areas within the default LZ3 may be designated as LZ4 by the local jurisdiction for high-intensity nighttime use, such as entertainment or commercial areas or areas with special safety concerns that require very high light levels.Special areas and government-designated parks within the default LZ3 area may be designated by local jurisdictions as LZ1 or LZ2; there is no size limit whatsoever.
LZ4Each local jurisdiction has its own decisionsEach local jurisdiction has its own decisions.Not applicable.Not applicable.
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Hao, Y.; Wang, P.; Zhang, Z.; Xu, Z.; Jia, D. A Review of the Characteristics of Light Pollution: Assessment Technique, Policy, and Legislation. Energies 2024, 17, 2750. https://doi.org/10.3390/en17112750

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Hao Y, Wang P, Zhang Z, Xu Z, Jia D. A Review of the Characteristics of Light Pollution: Assessment Technique, Policy, and Legislation. Energies. 2024; 17(11):2750. https://doi.org/10.3390/en17112750

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Hao, Ying, Peiyao Wang, Zhongyao Zhang, Zhiming Xu, and Dagong Jia. 2024. "A Review of the Characteristics of Light Pollution: Assessment Technique, Policy, and Legislation" Energies 17, no. 11: 2750. https://doi.org/10.3390/en17112750

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