The Economics of Space Sustainability
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3. Valuing the cost of space debris: the loss of Korean satellites in low-earth orbit
Abstract
Space debris presents an increasing challenge to the sustainable use of Earth’s orbits, particularly for emerging space nations like Korea. This chapter delves into the often-neglected social value of non-market satellites at risk from space debris within the Korean context and uses contingent valuation to quantify the costs of a space debris incident involving an earth observation satellite. The findings underline the profound significance of these satellites to national welfare and indicate that space debris can lead to substantial social costs.
Introduction
Technological advances and the ongoing expansion of space-faring entities have brought the issue of space debris and the potential for Kessler’s syndrome to the fore (Kessler, 1991[1]; Kessler and Cour‐Palais, 1978[2]). This trajectory of development and the challenges it brings call for an understanding of the Earth’s orbits as a global common-pool resource, (or as an extension of the Earth’s ecosystem) and an international conversation on their sustainable management (Lawrence et al., 2022[3]; Morin and Richard, 2021[4]; Newman and Williamson, 2018[5]). Previous dialogues have resulted in several milestones, such as the Inter-Agency Debris Coordination Committee (IADC) Space Debris Mitigation Guidelines (IADC, 2007[6]), and the Guidelines on the Long-term Sustainability of Outer Space Activities (UNOOSA, 2018[7]). Further discussions regarding how best to implement these sustainability practices have also been launched.
An important building block is to clearly understand the costs associated with space debris. Many current business models in the space sector do not incorporate social costs into their decision making processes, resulting in environmental externalities. In economic theory, such externalities can be addressed by introducing an appropriate economic instrument (e.g. a Pigouvian tax) that levies a cost amounting to the environmental damage caused. However, accurately quantifying the costs remains challenging, especially when market prices do not exist or do not fully reflect societal values. Satellites serving public purposes (hereafter “public satellites”), such as climate monitoring, disaster management, and/or national defence, are prime examples. Given that these satellites often have missions tailored to specific national needs, establishing a common measurement for their value becomes even more complex.
However, previous literature has often overlooked public satellites, mainly focusing on commercial satellites (Bongers and Torres, 2023[8]; Rao, Burgess and Kaffine, 2020[9]). This implies that the potential loss faced by countries that predominantly manage public satellites has been largely neglected. Considering that the loss of public satellites affects the broader societal welfare and national interests of a country, the blind spot may be much larger than anticipated. The key contribution of this chapter is to place a spotlight on the lost value of public satellites.
The scope of this study is limited to Korean satellites in low-earth orbit (LEO), where the risks posed by space debris are highest. As all current and planned satellite operations were found to have been assigned earth observation missions, this study specifically quantifies the potential lost value of Korean earth observation satellites in LEO due to space debris incidents. The focus lies on non-market valuation, such as the scientific, governmental, and public benefits provided by the satellites in question. Nonetheless, the results tie back to the global challenge of estimating the cost of space debris, given that the most significant impact of space debris at this time is the destruction and subsequent loss of functionality of satellites.
While the geopolitical context of Korea is distinct, which may amplify public concerns and the sense of loss from critical collision events to a certain extent, the results of the study can provide valuable insight into what is at stake for emerging space players. For instance, the loss of a single satellite can carry considerably more weight for such countries as they run a limited number of satellites. Given such local and global implications, this study can be instrumental in informing policy, directing resources effectively, and strengthening international co-operation to ensure the sustainable use of the Earth’s orbits.
In the following section, the research method, including data collection and scenario design, is described. The authors subsequently explain their estimation model, followed by the analysis of results, before discussing the implications and conclusions of the study.
Methodology
Contingent valuation
This study estimates the socio-economic costs arising from the damages caused by space debris using contingent valuation (CV), which elicits willingness-to-pay (WTP) for a contingent commodity based on survey responses. The method holds particular strength in revealing the value of non-market goods and services that are not directly traded in the market and, hence, where traditional market data is sparse. Public satellites fall into this category, as they are predominantly characterised by their public purpose and, thus, the benefits they provide lie largely beyond the realm of market transactions. Another advantage of CV lies in its ability to measure total economic value. This implies that the WTP estimate can serve as a comprehensive assessment of a commodity’s value, encompassing both use and non-use values.
Meanwhile, the utmost care must be given in all steps of the process, from defining the contingent commodity to designing and administering the survey, to ensure that the results of the CV study are robust. In accordance with Carson (1998[10]), who underscored the importance of shaping the contingent commodity to hold relevance within the local context, this study chose to estimate the cost of space debris through the value attached to preventing the loss of Korean earth observation satellites in LEO due to space debris incidents. In the scenario, the subject of valuation was materialised into a satellite protection programme. The remaining sections of this chapter elaborate on the subsequent procedures for conducting the survey.
Table 3.1. Survey overview
|
Main survey |
---|---|
Population |
All households in Korea |
Survey period |
7-14 August 2023 |
Sampling method |
Quota sampling based on age, region, and gender |
Sample size |
1 028 |
Protesters |
183 (17.8%) |
Survey mode |
Web-based survey |
Elicitation method |
Single-bounded dichotomous choice (SBDC) |
Payment vehicle |
Increased income tax (entirely allocated to a Satellite Protection Fund) |
Time frame of payment |
One-time payment |
Valued goods |
Lost value of Korean earth observation satellites in the low-earth orbit due to space debris incidents |
Contingent commodity |
Avoiding the loss of satellites due to space debris |
Policy options |
Satellite protection programme (radar, thruster, shield) |
Bid offered |
KRW 1 000, 5 000, 10 000, 20 000, 30 000 EUR 0.7, 3.7, 7.4, 14.7, 22.1 |
Note: 1. EUR 1 = KRW 1 358 (European Central Bank, 2023) 2. Currency conversion is rounded to the first decimal place.
Data collection
The sample consisted of a panel provided by a leading survey agency in Korea. To ensure it accurately represented the general population, the authors adopted quota sampling, based on age, gender, and region.
Due to cost and time constraints, a web-based survey was chosen as the method of data collection (see Table 3.1). A total of 1 032 responses were collected from 7 August to 14 August, but four observations were discarded during the preliminary data cleaning phase: two that indicated they had no annual income, including pensions and unearned income, and two that reported household sizes of 15 or more members. Therefore, the final sample consisted of 1 028 respondents. A comparison of the sample’s demographic characteristics with the general population confirmed that the sample was representative in terms of age, gender, and region (see Appendix A).
Survey development and design
Focus groups
The focus groups were carried out in three stages, held on 25 March, 29 April and 24 June, respectively. Each focus group had 5~7 participants, carefully selected to represent diverse backgrounds. The majority had little or no prior knowledge of orbital debris. Given this general lack of familiarity, the first two rounds focused on gauging the average level of interest and knowledge on the topic, as well as identifying key concerns when provided with information on the deteriorating environment in LEO. The second stage concentrated on observing participants’ responses to the draft scenario, with particular attention to the issue of credibility. The final stage centred on receiving feedback on the final draft of the survey to ensure that respondents could comprehend all contents clearly.
Pilot survey
The pilot survey was conducted online from 26 July to 27 July, during which 201 responses were collected. The primary purpose was to evaluate the potential response and protest rates, suitable bid levels, and whether any modifications were needed. According to the results, no significant changes were deemed necessary, with a moderate protest rate of 5.5%. In terms of bid levels, respondents were presented with an open-ended question to establish a range of acceptable bid amounts. This process led to the identification of five bid levels, which were determined based on the 15th to 85th percentile range of the responses. These bid levels were set at KRW 1 000 (EUR 0.7), KRW 5 000 (EUR 3.7), KRW 10 000 (EUR 7.4), KRW 20 000 (EUR 14.7), and KRW 30 000 (EUR 22.1). These bid amounts represent incremental increases over the current tax levels that respondents are paying.
Questionnaire
The questionnaire consisted of four sections. The first section was intended to warm up respondents by asking them about their attitudes toward various government policies. The following section presented the scenario with information on the current state of debris in LEO, followed by the dichotomous choice question and debriefing questions to identify protest bidders. The third section asked about attitudes toward science, technology and the environment, as variables potentially correlated with one’s response. The final section collected demographic information, including gender, age, parental status, education level, occupation, and religious belief.
A distinctive feature of the survey was that the scenario was presented in three short videos. This approach was considered advisable to facilitate engagement with and understanding of a scenario involving unfamiliar, distant, and complex subject matters (i.e., objects in outer space and new space technology). To ensure that the information was perceived and processed, respondents were not allowed to skip through the video and were required to take a follow-up quiz that recapitulated the most crucial segments. If so desired, they could replay the video.
Scenario
The scenario began by describing the launch plans for Korea within the next three years. As all the country’s satellites currently in orbit (i.e., four earth observation satellites) would reach the end of their lifetimes by 2025, they were to be replaced by new ones developed with enhanced skills and technology. In the baseline scenario, however, orbital debris and the likelihood of a critical collision event were expected to increase quickly, to the extent that all the newly launched satellites would lose their functionality within ten years. The implication was a serious threat to national security, broadly defined to encompass disaster and climate change management, public safety, national defence, food security, and land management.
The policy option included measures to predict, prevent and mitigate the impact of space debris incidents. In order to minimise bias, emphasis was put on the fact that the policy would not lead to technological advancement within the country, instead benefitting from products and services already available in the market. In the alternative scenario, in which the policy is adopted, all the newly launched satellites were expected to remain fully functional for the next ten years. The payment vehicle was a one-time tax payment that would be contributed to a national fund designated for the sole purpose of protecting the country’s satellites. Bid amounts, determined based on the results of the pilot survey, were randomly assigned from the five options listed above.
In developing the scenario, the authors actively sought advice from experts and scientists in the space sector to ensure that the contents were sound from both scientific and policy perspectives. For further information on the scenario presented to respondents, see Appendix B.
Model estimation
The elicitation method of this study was single-bounded dichotomous choice (SBDC). Given the method, this section first explains the conventional approach of estimating WTP, then describes the baseline model of this study, which better accounts for protest responses (i.e. zero bids motivated by protest behaviour).
Conventional approach
According to the random utility framework and assuming that preferences are linear in income and covariates (Haab and McConnell, 2002[11]; Hanemann, 1984[12]), the respondent ’s indirect utility can be expressed as:
where is respondent ’s utility with () or without () the change, is the vector of personal or household characteristics, is income, and are unobserved preferences. A respondent will accept the bid (i.e. answer ‘yes’) if they enjoy higher utility in the alternative scenario with the policy, despite the loss of utility from paying the offered bid, . Therefore, the response probability (i.e. the probability of answering ‘yes’) is:
where , , and .1 Assuming further that is independently and identically distributed and follows a standard normal distribution, the response probability can be estimated with the binary probit model as:
where is a standard normal distribution function, is the standard deviation of the error term, and and are the parameters of interest.
Given the above, the parameter estimates can be obtained by maximising the following log-likelihood function:
where if respondent answers ‘yes’.
The expected value of WTP for respondent , which renders them indifferent between the baseline and alternative scenario, can be found by using eq. (1) and conditioning on the parameters as:
The mean WTP, , is an expansion of eq. (5) over the entire sample and can be calculated with the parameter estimates from eq. (4) and confidence intervals following the procedures of Krinsky and Robb (1986[13]).
Sample selection model
The conventional approach, however, may result in an under- or overestimation depending on how protest responses are treated.2 Including protest bids as ‘true zero’ WTP valuations risks underestimation, since the true WTP may be positive; on the other hand, excluding protest bids, as suggested by Mitchell and Carson (1989[14]), risks overestimation and the exclusion may introduce selection bias (Strazzera et al., 2003[15]). Therefore, this study adopts a sample selection model, which can produce more reliable WTP estimates. In this model, the respondent’s decision can be understood as a joint process, in which they first decide whether to reveal (or state) their WTP, then decide whether to accept the offered bid (Eom and Hong, 2009[16]; Strazzera et al., 2003[15]; Sun, Yuan and Yao, 2016[17]). The former is modelled by the latent variable , which is affected by a vector of respondent characteristics, , while the latter is modelled by the latent variable , which also depends on a vector of respondent characteristics, .
where and are error terms.
Whilst neither nor are observed, the respective decisions are, thus allowing the joint process to be modelled as Eq. (8). A respondent will reveal their WTP () if the utility of doing so is greater than or equal to zero () and they will accept the bid () if their WTP at least amounts to the bid, .
Accordingly, the likelihood function can be expressed as
Assuming the joint distribution of follows a bivariate normal distribution with mean zero and the variances of and are normalised to 1, the log-likelihood is:
where denotes the correlation coefficient between and (Brouwer and Martín-Ortega, 2012[18]). The mean WTP in the sample selection model is calculated by maximising the above equation, which is comparable to eq. (4) in the conventional approach.
Results
Descriptive statistics
Table 3.2 provides the statistical summary of the survey sample. Beginning with the demographic variables, the average age of respondents hovered around 48 years. Gender representation was balanced, with males and females each making up roughly 50% of the sample. Respondents reported an average annual household income of KRW 56.05 million (EUR 41 274). For education level, where 1 indicates the completion of a 4-year university programme or above and 0 otherwise, 64% of the respondents were found to be highly educated. Finally, the average household size was about three members.
Attitudinal variables were included to capture an individual’s awareness, beliefs, and trust in various areas of relevance. 61% indicated prior awareness of the concept of “space debris.” Among these informed participants, 71% traced their source to television or newspapers, while 21% referred to YouTube. Environmental attitudes were measured using Dunlap’s revised New Ecological Paradigm (NEP) scale, which includes 15 items probing one’s ecological worldview (Dunlap et al., 2000[19]). After reverse coding the even-numbered items, so that a higher score represents stronger alignment with the ecological paradigm, and summating the scores of all items, the average score settled at 55 out of 75 points.
The survey also incorporated six items from the “Science and Technology” section of the World Value Survey to assess respondents’ perceptions of science and technology (Haerpfer et al., 2022[20]). Using reverse coding to ensure that higher scores indicate more positive views, the average score was observed to be 40 out of 60 points. Lastly, participants were asked to rate their level of trust in government-led policy projects on a 5-point Likert scale, where 1 signifies the least amount of trust and 5, the maximum. The average trust score was 2.7, implying a moderate level of trust in government.
Table 3.2. Summary statistics
Variable category |
Variables |
Mean |
Standard deviation |
Min-max |
---|---|---|---|---|
Demographic |
Age |
47.83 |
14.54 |
19 - 79 |
Gender (male = 1) |
0.50 |
0.50 |
0 - 1 |
|
Household income |
5 605 |
4 046 |
0 – 40 000 |
|
Education level |
0.64 |
0.48 |
0 - 1 |
|
Household size |
3.01 |
1.31 |
1 - 9 |
|
Attitudinal |
Awareness of space debris |
0.61 |
0.49 |
0 - 1 |
Environmental attitude |
54.55 |
7.45 |
36 - 75 |
|
Attitude toward science |
40.09 |
6.77 |
17 - 60 |
|
Trust in government |
2.69 |
0.94 |
1 - 5 |
N = 1 028. The annual income is displayed in units of KRW 10 000.
Protest response
Among the total of 1 028 respondents, 221 (21.5%) indicated a zero WTP. In order to discern protest bids from true zero bids, the survey included a debriefing question seeking to understand the reasons behind the zero response (Table 3.3). The options were presented randomly, with the exception of “other” which always appeared last, to guard against potential order effects. The results revealed that a significant 82.8% of the zero bids were protest bids, amounting to 17.8% of the entire sample.
Table 3.3. Identification of zero-value bids
|
|
Items |
.Frequency |
% |
---|---|---|---|---|
True zero willingness-to-pay |
1 |
I cannot afford to pay |
23 |
10.4 |
2 |
Protecting satellites holds no value for me |
3 |
1.4 |
|
3 |
Our society faces more pressing issues than satellite problems |
9 |
4.1 |
|
4 |
Other |
3 |
1.4 |
|
Subtotal |
38 |
17.3 |
||
Protest bids |
5 |
The survey lacks sufficient information to make a judgement |
6 |
2.7 |
6 |
The government should address the problem with the taxes already collected |
95 |
43.0 |
|
7 |
Those causing the problems, not the general public, should bear the costs |
9 |
4.1 |
|
8 |
It's doubtful that funds will be exclusively used for the ‘satellite protection programme’ |
23 |
10.4 |
|
9 |
The government plan is not trustworthy |
50 |
22.6 |
|
Subtotal |
183 |
82.8 |
||
Total |
221 |
100 |
To investigate the systemic nature of these protest bids, the authors constructed two probit models, in which the dependent variable is set as 1 for protesters and 0 for those revealing their WTP. Model (1) includes only demographic variables, while model (2) further includes attitudinal variables.
As shown in Table 3.4, in model (1), the results suggest that younger individuals and males are more inclined to submit a protest bid. However, with the introduction of attitudinal variables in model (2), the significance of both the age and gender variables fades. Instead, environmental attitudes, attitudes toward science, and trust in government all surface as statistically significant variables with negative coefficients. This implies that individuals with weaker environmental attitudes, less favourable perceptions of science, and lower trust in government are more likely to give protest responses. Overall, the results indicate that simply removing protesters from the sample may lead to selection bias, since the protests are systematically influenced by certain socio-economic and attitudinal factors.
Table 3.4. Determinants of protest bids
Variable category |
Variables |
(1) |
(2) |
||
---|---|---|---|---|---|
Coefficient |
Standard error |
Coefficient |
Standard error |
||
Demographic |
Age |
-0.01** |
0.00 |
-0.00 |
0.00 |
Gender (male = 1) |
0.16* |
0.09 |
0.14 |
0.10 |
|
Household income |
-0.00 |
0.00 |
0.00 |
0.00 |
|
Education level |
0.06 |
0.10 |
0.13 |
0.10 |
|
Household size |
-0.02 |
0.04 |
-0.03 |
0.04 |
|
Attitudinal |
Awareness of space debris |
-0.12 |
0.10 |
||
Environmental attitude |
-0.01** |
0.01 |
|||
Attitudes toward science |
-0.01* |
0.01 |
|||
Trust in government |
-0.42*** |
0.06 |
|||
Intercept |
-0.60*** |
0.22 |
1.62*** |
0.51 |
|
N |
1 028 |
1 028 |
|||
Pseudo R2 |
0.01 |
0.08 |
|||
Log-likelihood |
-476.39 |
-441.43 |
Note: *** p<0.01, ** p<0.05, * p<0.1.
Willingness to pay to avoid the loss of satellites
Three distinct models were used to estimate the WTP for protecting satellites from space debris incidents (Table 3.5). Models (1) and (2) both follow the conventional approach using the binary probit model. However, they differ in that the former includes the entire sample, while the latter excludes the 183 protesters, each with its own shortfalls. In model (1), the mean WTP, estimated as KRW 20 443 (EUR 15.05), risks underestimation since the protesters may genuinely be willing to contribute. Model (2) resulted in a significantly higher mean WTP of KRW 32 755 (EUR 24.12), but risks selection bias by overlooking the systematic occurrence of protesters.
Considering the limitations of both models, the authors turned to model (3), a bivariate sample selection model. In this model, a respondent’s decision is understood as a joint process of deciding whether to reveal one’s WTP and whether to accept the offered bid. The correlation coefficient, ρ, signifies the potential degree of sample selection and, when positive, implies that eliminating protesters may introduce systematic bias that leads to an overestimation of the mean WTP. With a positive and significant ρ of 0.99, model (3) estimated a mean WTP of KRW 21 171 (EUR 15.59), which was selected as the most representative result in the context of this study.
Across all models, the variables having a statistically significant impact on WTP remained consistent. The bid variable was inversely correlated with WTP at a 0.01 significance level, in accordance with the fundamental notion that higher payments reduce the chances of a ‘yes’ response. As for the demographic variables, age and household income showed positive coefficients, indicating that older people and those with higher household income are more willing to pay. A notable discovery was the positive correlation between environmental attitudes and WTP. This suggests that individuals with stronger environmental attitudes, or holding attitudes closer to the ecological paradigm, may extend their concerns beyond the boundary of our planet, giving support to the argument that the Earth’s orbits constitute an extended ecosystem or, at the least, are a form of common-pool resources (Lawrence et al., 2022[3]; Morin and Richard, 2021[4]). The positive correlation between attitudes toward science and WTP at the 0.01 significance level indicates that the more an individual is interested in science and believes science benefits society, the higher their WTP for satellite protection. The same was found for individuals with higher levels of trust in government.
Table 3.5. Results of parameter estimation
Variable |
(1) Full sample |
(2) Protesters removed |
(3) Sample selection |
|||
---|---|---|---|---|---|---|
Coefficient |
Standard error |
Coefficient |
Standard error |
Coefficient |
Standard error |
|
Selection eq. |
||||||
Age |
0.00 |
0.00 |
||||
Gender (male= 1) |
-0.17* |
0.10 |
||||
Household income |
0.00 |
0.00 |
||||
Education level |
-0.11 |
0.10 |
||||
Household size |
0.03 |
0.37 |
||||
Awareness of space debris |
0.14 |
0.10 |
||||
Environmental attitude |
0.01* |
0.01 |
||||
Attitude toward science |
0.01* |
0.01 |
||||
Trust in government |
0.41*** |
0.06 |
||||
Constant |
-1.45*** |
0.51 |
||||
Elicitation eq. |
||||||
Bid |
-0.00*** |
0.00 |
-0.00*** |
0.00 |
-0.00*** |
0.00 |
Age |
0.02*** |
0.00 |
0.02*** |
0.00 |
0.02*** |
0.00 |
Male |
-0.03 |
0.08 |
0.06 |
0.10 |
-0.01 |
0.08 |
Household income |
0.00** |
0.00 |
0.00** |
0.00 |
0.00** |
0.00 |
Education level |
-0.09 |
0.09 |
-0.04 |
0.10 |
-0.09 |
0.09 |
Household size |
0.02 |
0.02 |
0.00 |
0.04 |
0.01 |
0.03 |
Awareness of space debris |
0.02 |
0.02 |
-0.04 |
0.10 |
0.02 |
0.09 |
Environmental attitude |
0.02*** |
0.02 |
0.02*** |
0.01 |
0.02*** |
0.01 |
Attitude toward science |
0.03*** |
0.01 |
0.03*** |
0.01 |
0.03*** |
0.01 |
Trust in government |
0.36*** |
0.05 |
0.23*** |
0.05 |
0.35*** |
0.05 |
Constant |
-3.69*** |
0.46 |
-3.13*** |
0.53 |
-3.72*** |
0.45 |
ρ |
0.9999 |
0.001 |
||||
N |
1 028 |
845 |
1 028 |
|||
Pseudo R2 |
0.12 |
0.11 |
n.a. |
|||
Log-likelihood |
-623.98 |
-478.02 |
-918.99 |
|||
Mean willingness-to-pay |
KRW 20 443 (EUR 15.05) |
KRW 32 755 (EUR 24.12) |
KRW 21 171 (EUR 15.59) |
Notes: *** p<0.01, ** p<0.05, * p<0.1. n.a.: not applicable. In the selection equation, the dependent variable was 1 for true responses (n=845) and 0 for protest responses (n=183). EUR 1 = KRW 1 358 (European Central Bank, 2023).
The aggregated benefit
The aggregated benefit was derived by multiplying the mean WTP by the total population of beneficiaries. Using the estimate from model (3) from Table 3.5 and by conducting 10 000 bootstrapping iterations in accordance with Krinsky and Robb’s (1986[13]) simulation method, the aggregate benefit was estimated as KRW 502 billion (EUR 369.6 million). This figure represents the social cost borne by Korean citizens when the country’s earth observation satellites are lost for ten years, following a critical collision event with space debris. It is important to note that the estimated lower and upper bounds provided in Table 3.6 are derived from the 95% confidence interval of the Monte Carlo simulation.
Table 3.6. Aggregated benefits
|
Lower bound |
Mean |
Upper bound |
---|---|---|---|
Willingness-to-pay |
KRW 16 540 (EUR 12.2) |
KRW 21 171 (EUR 15.6) |
KRW 28 705 (EUR 21.1) |
Population (number of households) |
23 705 814 |
||
Total benefit |
KRW 392.1 billion (EUR 288.7 million) |
KRW 501.9 billion (EUR 369.6 million) |
KRW 680.5 billion (EUR 501.1 million) |
1. The population data is drawn from Ministry of Public Administration and Security (2022). 2. EUR 1 = KRW 1 358 (European Central Bank, 2023)
Discussion and conclusions
The looming threat of space debris and its potential implications, especially for emerging space nations, urgently calls for the sustainable use of the Earth’s orbits. This, in turn, requires a clear understanding of the costs of space debris and a comprehensive viewpoint that encompasses the diversity of space entities and objects. As one such effort, this study has explored the challenge of estimating the often overlooked social value of non-market satellites at risk due to space debris, focusing on the case of Korea. Given the pivotal roles public satellites serve, such as in the areas of climate monitoring, disaster management and national defence, the potential damage can have deep economic, strategic, and societal impacts.
This study quantifies the cost of space debris incidents involving earth observation satellites, determining a mean WTP of KRW 21 171 (EUR 15.6) per household. This amounts to an aggregated value loss of KRW 501.9 billion (EUR 369.6 million) over a decade for Korean LEO satellites. A key distinction is its singular focus on public satellites, launched for the purpose of serving the larger public interest and increasing the nation’s collective welfare. This divergence from commercial considerations inherently led to the adoption of a non-market valuation methodology, another differing aspect. In light of the above, the magnitude of the results can be understood to indicate the profound implications these satellites have for national welfare.
From a policy perspective, these figures not only capture the considerable disutility that can be caused by space debris but also signal a broad social consensus in favour of allocating resources for mitigating the problem. On the economic front, the study provides a tangible monetary assessment using CV, bridging the gap between distant and abstract objects in outer space and people inhabiting Earth. Should this inspire other studies, they will collectively facilitate a better understanding of the economic impacts of space debris and other issues arising in the space environment, enabling policy makers to better prioritise and design interventions, based on empirical evidence rather than mere speculation.
Despite these findings, many paths remain untaken in the field of space sustainability. Further research could explore in more detail the different functions and applications of satellites, as well as the ramifications of their loss. Broadening the scope to other countries could lend comparative insights that can enrich global discussions.
At a time when the race to harness the potential gains from outer space is intensifying, this research offers both a framework for informed policy making and a stepping stone for future academic work. While the study concentrates on Korea, the findings may resonate with newcomers to the space economy and contribute to building a collective understanding of the risks of space debris for the international community, tasked with strengthening co-operation for improved space traffic management and maintaining a sustainable space environment for current and future generations.
Endnotes
References
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Annex 3.A. Sample representativeness of the survey
Annex Table 3.A.1. Sample representativeness of the survey
Characteristics |
Sample (N = 1 028) |
Population (Korea) |
|||
---|---|---|---|---|---|
Sample size |
Proportion (%) |
Population |
Proportion (%) |
||
Gender |
Male |
509 |
49.5 |
21 657 711 |
49.6 |
Female |
519 |
50.5 |
22 037 245 |
50.4 |
|
Total |
1 028 |
100 |
43 694 956 |
100 |
|
Age |
19-29 |
165 |
16.1 |
6 908 937 |
15.8 |
30-39 |
157 |
15.3 |
6 615 511 |
15.1 |
|
40-49 |
185 |
18.0 |
8 073 117 |
18.5 |
|
50-59 |
203 |
19.8 |
8 612 064 |
19.7 |
|
60 and older |
318 |
31.0 |
13 485 327 |
30.9 |
|
Total |
1 028 |
100 |
43 694 956 |
100 |
|
Region |
Seoul |
191 |
18.6 |
8 220 164 |
18.8 |
Busan |
69 |
6.7 |
2 874 159 |
6.6 |
|
Daegu |
49 |
4.8 |
2 012 860 |
4.6 |
|
Incheon |
60 |
5.8 |
2 514 038 |
5.8 |
|
Gwangju |
29 |
2.8 |
1 189 664 |
2.7 |
|
Daejeon |
29 |
2.8 |
1 218 773 |
2.8 |
|
Ulsan |
21 |
2.0 |
926 012 |
2.1 |
|
Sejong |
10 |
1.0 |
292 436 |
0.7 |
|
Gyeonggi-do |
267 |
26.0 |
11 355 976 |
26.0 |
|
Gangwon-do |
30 |
2.9 |
1 322 365 |
3.0 |
|
Chungcheongbuk-do |
30 |
2.9 |
1 354 735 |
3.1 |
|
Chungcheongnam-do |
42 |
4.1 |
1 788 033 |
4.1 |
|
Jeollabuk-do |
36 |
3.5 |
1 509 155 |
3.5 |
|
Jeollanam-do |
36 |
3.5 |
1 557 796 |
3.6 |
|
Gyeongsangbuk-do |
52 |
5.1 |
2 237 251 |
5.1 |
|
Gyeongsangnamdo |
65 |
6.3 |
2 762 267 |
6.3 |
|
Jeju-do |
12 |
1.2 |
559 272 |
1.3 |
|
Total |
1 028 |
100 |
43 694 956 |
100 |
Note: “Population” refers to the count of individuals in South Korea aged 19 or older.
Source: The population data by age was retrieved on Aug 18, 2023, from: Ministry of Public Administration and Security. (2023). Status of Population by Age. https://jumin.mois.go.kr/ageStatMonth.do.
Annex 3.B. Scenario details
Annex Figure 3.B.1. Image of the new satellites to be launched
![](/adobe/dynamicmedia/deliver/dm-aid--634a396d-8c28-4ab1-a7f0-4b277eecd470/image2.png?quality=80&preferwebp=true)
Description: “The development of the new satellites was led by our country using the most advanced technology. KOMPSAT-6 can observe the Earth in any weather condition. KOMPSAT-7 and KOMPSAT-7A can provide 30cm resolution imagery, which matches the best level found across the globe. CAS500-2 is a medium satellite optimised for land management.”
Annex Figure 3.B.2. Image of satellite services
![](/adobe/dynamicmedia/deliver/dm-aid--e4e26e65-b522-438b-a5b0-351e676c6013/image3.png?quality=80&preferwebp=true)
Description: “The satellites hold important missions for the country’s management. Firstly, they provide information necessary for disaster response, such as in the case of a typhoon, flood, or landslide. Secondly, they provide information used to respond to severe effects of climate change, such as urban heat islands, the rise of sea surface temperatures, and widespread damage to crops. Thirdly, they provide information crucial for national defence, such as the status of neighbouring countries. Lastly, they provide geographic information for the public.”
Annex Figure 3.B.3. Image of the Space Protection Programme
![](/adobe/dynamicmedia/deliver/dm-aid--2bdaa3fe-2e4a-4d0e-b52a-2c3296650c17/image4.png?quality=80&preferwebp=true)
Description: The scientific community suggests three measures to avoid critical collision events with space debris, which together compose the satellite protection programme. The first is prediction. This can be done by subscribing to an existing service that analyses the trajectories of satellites and space debris, using radars in various locations across the globe, and predicts potential collisions. The second is prevention. This can be done by attaching a thruster to satellites, which can effectively prevent collisions by adjusting a satellite’s orbit away from approaching space debris. The third is mitigation. This can be done by adding verified shielding, which protects satellites from inevitable collisions. Such shielding technologies have been used by leading space-faring countries and for the International Space Station.