5.1. The Basic Orientations Established in International Environmental Law
Concerning, first, the obligation of states to utilize scientific data within policymaking processes, one may note that already in the early 90s, the UN Framework convention on Climate Change (1992, UNFCCC)
16 first mentioned scientific knowledge by highlighting that “lack of full scientific certainty should not be used as a reason for postponing” measures to address climate change (Art. 3.3). In this sense, a twofold duty of states was created to, on the one hand, address climate change in an effective manner and avoid any recourse to (easy) excuses and, on the other hand, develop and use science in the best possible way. Following on from that, the Kyoto Protocol (adopted in 1997, entered into force in 2005)
17, inter alia, was built upon science to define and clarify states’ obligations to reduce emissions (Annex A of the Protocol). However, a few years later, this objective was still not reached, and the IPCC admitted in 2007 that the warming of the climate system is “unequivocal” (
IPCC, 2007). As a response, the obligation to make maximum use of the possibilities offered by the best available science was strengthened in the Paris Agreement (2015), laying down that in adopting related policies, states must consider, as well as share and develop, scientific knowledge on and understanding of climate change (e.g., Art. 7.5 and 14.1)
18.
Importantly though and parallel to that (second), dedicated bodies were also created right from the outset to facilitate and encourage the collection and use of scientific data. By way of illustration, in 1988, the United Nations Environmental Program (UNEP), which had been launched at the 1972 Stockholm conference, and the World Meteorological Organization (WMO) agreed upon the creation of the International Panel on Climate Change (IPCC) to assess the available climate-related information
19 and formulate response strategies (Art. 1). The IPCC was maintained under the UNFCCC (Art. 21), and its role was strengthened further. At the same time, the UNFCCC also established the Subsidiary Body for Scientific and Technological Advice (SBSTA) to assist the decision-making organ (Conference of the Parties/COP) in using scientific knowledge, such as by providing it with relevant advice and information, opinions on climate-related technologies, etc. (see, e.g., Art. 9.2.a and Art. 9.2.b). Finally, the Paris Agreement created teams of experts entitled to review the consistency of scientific (climate-related) information submitted by state parties (Art. 13.11). In this context, it is noteworthy that the latter treaty additionally laid down the rule that states should strengthen “institutional arrangements, including those under the Convention …” (Art. 7.7.b). Thus, in an indirect though clear manner, the duty was established to also create national bodies and tools that would be competent to support the work conducted by the international specialized authorities mentioned above, in a scientific and sustainable way.
Following on from that, one may observe that emphasis was put on developing specialized tools and authorities that would allow for the participation of all actors involved to assist policymakers; in reality though, the idea mostly applied to global initiatives (e.g., campaigns, structured partnerships), city alliances or networks, regional initiatives, etc. (
UNEP, 2023). In other words, the individual, namely the citizen per se, appears to be absent from being actively involved in this framework, although it was clearly established from the outset that “Man has the fundamental right to … adequate conditions of life, in an environment of a quality … and he bears
a solemn responsibility to protect and improve the environment for present and future generations” (Stockholm Declaration Principle 1; emphasis added)
20. In truth, legal tools to achieve this objective were soon adopted, such as the procedural right of access to (climate-related) information or the right to public participation, as it is presented in the 2019 UNEP Frist Report on the Environmental Rule of Law
21. However, human rights organizations denounce the fact that citizens (individually) have been denied the right of access to climate-related information or have even reported cases of “climate science censorship” (
ARTICLE 19, 2009). Consequently, the prevailing impression is that individuals remain largely excluded from active participation within the existing system.
At the same time, given the proliferation of new scientific tools (such as open data platforms utilizing mobile applications and the Internet of Things, as explained below), one may argue that there is significant potential to enhance citizen involvement by leveraging, e.g., the accessibility, continuity, quality, and affordability of scientific means. The only question that remains to be answered is what form citizens’ interaction and participation in climate-change decision-making could take, especially taking into account that the issue of citizens’ coproduction in fields of public policy, lato sensu, has already raised concerns as to its precise implementation (e.g., in the context of health, see
Koch et al., 2024).
Therefore, in addressing this challenge, it is worth considering that scientific and technological advancements have also considerably facilitated the development of open data platforms and climate data store APIs (application programming interfaces), enabled the aggregation of climate information, and enhanced predictive capabilities and the monitoring of climate trends in specific regions, while fostering opportunities for citizen involvement.
5.2. Technological Advances: Enabling Citizen Participation in Climate Monirtoring
The international legal framework described above has allowed states to first understand the potential of science in tackling climate change and adapting/mitigating its impacts, and also to encourage the development and use of green devices and infrastructure. Hence, based on the idea that the development and use of technology is an international priority—and of vital importance for tackling climate change, such as in the case of clean energy devices (UNFCCC 2016)
22—states have tried to also make the most of space systems and Earth Observation (EO) data, as policymakers recognized the capital importance of such information for the monitoring and management of everyday activities, including natural phenomena and/or climate-related crises (
Salin, 1992;
Corvino et al., 2019;
Rapi et al., 2019;
Koskina et al., 2023). In this context, Artificial Intelligence (AI) has allowed us to further optimize the use of existing EO datasets, inter alia (
Gal et al., 2020), and better anticipate, for instance, droughts (
Sardar et al., 2021) and wildfires (
Kondylatos et al., 2022). As a result, initiatives were taken to create international databases that would ensure access to scientific information (
ESA, 2023), containing data, like in the case of those delivered by the EU system “Copernicus”
23, that are available to citizens on a free, full, and open basis. In addition to that, states have put effort into improving their climate governance frameworks, such as by adopting climate laws setting goals that include emission reduction targets or short-term actions and measures, and more recently, they have also established climate change (advisory) bodies based on a multidisciplinary representation in climate-related areas of expertise (note that dedicated authorities may take different forms; still, they all aim at “injecting science into the policy-making process and enhance governmental accountability”) (
Evans & Duwe, 2021, p. 8).
More precisely, technological changes in the cleantech and green technology domain span a wide range of technological fields. Indeed, energy transitions require fundamental and long-term infrastructures, new enabling technologies, and long-time periods (
Smil, 2017,
2022). Fossil fuels remain a dominant energy source, while solar and wind remain a smaller part of the mix (
Smil, 2021). Concurrently, in the domain of energy transitions, technological innovations and policy design can accelerate technological change, while the energy transition may be a set of more discrete conversions (
Sovacool, 2016). Moreover, the diffusion of new technologies follows diverse ways, and it is strongly associated, inter alia, with technological readiness, techno-economic efficiency of technologies, and commercial applicability and demand, as well as the availability of critical inputs and converging technologies.
In particular, converging technologies constitute a new area of technological advancement. As a result, space technologies provide tools with which to monitor and analyze satellite data related to climate change, while Artificial Intelligence (AI) provides new approaches and predictions for major climate trends. Green technologies are inextricably interlinked with a vast array of digital and other key enabling technologies allowing efficient use of new applications in clean and sustainable technologies (e.g., low-carbon energy, renewable energy generation, energy storage solutions, smart grids).
Similarly, the diffusion and the deployment of key cleantech technologies are interlinked with legal, institutional, and social parameters. Major changes in the energy and cleantech sectors interact with key prerequisites in the institutional and policy environment. In this context, open data platforms and climate data store APIs (application programming interfaces) create opportunities for the aggregation of climate data and could feed the predictive capabilities or monitoring of climate trends in specific geographical areas. The exploitation of sensors and monitoring technologies from various sources provide multilevel data for temperature trends and weather forecasts for cities or rural areas. The rapid and extensive use of mobile applications and Internet of Things might provide new experimental approaches for collecting, triangulating, and analyzing multimodal datasets for climate parameters and potential impacts.
In this respect, policy experimentation should be part of the policy mix for institutional interventions. The appropriate mix of policy interventions might combine both horizontal policy strategic plans, programs, and measures (e.g., green policies in the EU, the USA, and China) and also topic-focused interventions and initiatives to develop converging technological applications, to pursue collaborative innovation, and to provide new governance schemes for climate change. Even more importantly, the co-evolution of legal and institutional arrangements with technological applications allow technological openness, technological inclusiveness, collaborative innovation, and science-focused data for climate change, which might create new avenues for accessible technologies for citizens encouraging participation and active engagement.
In other words, technological advances allow for the involvement of new stakeholders, such as citizens. For example, the use of Artificial Intelligence (AI); the availability of data aggregated from data platforms, Internet of Things (IoT), and satellite data; and new algorithmic systems, software applications, and AI-powered micro-processors provide opportunities for broader inclusion, even of micro-stakeholders. Indeed, the emerging technological context leaves room for the participation of minor actors in the science domain and policymaking process, such as individual citizens, by providing multi-layer data and inputs to address climate change. It is worth noting here that the direction and the character of technological change is not of deterministic nature. That is, the technological advances might have differentiated effects on production processes based on their characteristics. For example,
Acemoglu and Restrepo (
2019) described how new technologies not only increase the productivity of capital and labor but also impact the allocation of tasks to these factors of production; and under this prism, they illustrated the major differences between automation technologies that enable capital to be substituted for labor in a range of tasks (displacement effect) and factor-augmenting technologies that do not impact the task content of production (ibid.). Similarly, several emerging technologies or technological areas might reflect more inclusive characteristics depending on their use from end users (e.g., companies, citizens). A larger part of emerging technologies provides technical specifications allowing for the involvement of users, such as citizens, into the collection of data, providing real-time information and enriching multi-layer available knowledge for social and natural phenomena. Different set of technologies for differentiated uses of technological applications might enhance inclusive, interactive, and participative functions and roles for citizens, including them as new nodes of information into the science process and climate monitoring.
On top of that, technical, organizational, and further institutional dimensions allow for the deployment of “data networks”, data aggregation, data exploitation on the basis of interoperability and interconnection, and the use of AI-enabled decentralized technologies (e.g., blockchain-driven decentralization and distributed algorithm systems used as cryptographic methods to collect and manage data and digital twins for collecting climate-related data from multiple sources, such as citizens, smart sensors, and satellites).
