The consequences of climate change are some of the most pressing issues our world is facing at present and into the future. Scientists from a wide range of disciplines are repeatedly warning policy makers and the broader public about the emergency of curbing global climate change and its disastrous effects on the biosphere [1
]. Nevertheless, measures to prevent increasing greenhouse gas emissions (GHG) lack global and profound commitment. Since the first IPCC report in 1990, GHG-emissions have been steadily rising. At present they are even 60% higher than in 1990 [2
]. Therefore, it is not surprising that weather extremes are increasing year by year. According to projections, the frequencies of heat waves will further increase during the rest of the 21st century [3
]. This poses new health-related challenges worldwide, as it causes not only an increase in physical health effects (e.g., through temperature and pollution related illnesses) but also leads to mental health effects due to potential climate change-induced population displacement, the increase in vector-borne diseases, and threats to food and water security [4
Since 2009 “The Lancet Countdown on health and climate change” has contributed to increasing knowledge on climate change by monitoring adverse health effects. According to a conservative estimate, the repercussions of climate change may be directly or indirectly responsible for 5.5 million disability adjusted life years (DALYs) lost in 2000. This figure relates only to deaths caused by cardiovascular diseases, diarrhea, malaria, accidents caused by floods or landslides, and malnutrition [10
]. Regarding the scale and size of detrimental health effects, it seems evident that strategies to counter ongoing climate change need to become a core topic for political action in this century [11
Such strategies and related measures will undoubtedly be of particular importance in urban areas for two reasons: (1) Cities are densely populated regions. The level of urbanization, i.e., people living in urban areas, is expected to increase in the coming decades [12
]. Moreover, cities and their supply chains are major contributors of GHG emissions. On a global scale, cities are responsible for nearly three quarters of fossil fuel related GHG emissions [14
]. (2) Cities are hot spots of climate change effects. Due to grey infrastructure, they are highly vulnerable to the adverse effects of heat waves, since under these conditions, heat stress lasts longer not only during the day but also during night hours as buildings and sealed surfaces store heat. Vulnerable population groups, such as young children and the elderly, suffer particularly from climate change-induced alterations of human living conditions. In light of demographic change (i.e., ageing societies), the health burden will further increase in the coming decades [15
In this context, technological measures and nature-based interventions to improve the climate in urban spaces are gaining popularity. Scientific disciplines such as urban planning and architecture are thus becoming increasingly important to safeguard the well-being of urban populations as they are key to building up, expanding, and improving urban blue and green infrastructure. In contrast to grey infrastructure, which primarily consists of concrete, glass, and metal structures, green and blue infrastructure refers to natural and semi-natural landscape elements such as parks, trees, green facades, pools, or ponds. In recent decades, medicine-related disciplines including public health research also gained additional traction against this backdrop. The COVID-19 crisis has further increased the relevance of urban green infrastructure for human well-being in the public discourse. During COVID related lockdowns, green spaces in urban areas have been heavily used for recreational purposes, which has partly led to overcrowding [16
]. Different scientific disciplines (urban planning, architecture, public health, etc.) attempt to contribute with their specific forms of knowledge and epistemic practices to tackle the climate change induced challenges in urban spaces.
In general, scientific disciplines are organized as so-called epistemic communities. According to Haas, an epistemic community is “a network of professionals with recognized expertise and competence in a particular domain and an authoritative claim to policy-relevant knowledge within that domain or issue-area
], p. 3. Haas’ understanding of epistemic communities is oriented towards policy change and advice. In light of climate change, epistemic communities are fundamental for conceptualizing, planning, and implementing effective mitigation and adaptation measures. The role epistemic communities play for policy change and advice is reflected by four criteria of epistemic communities Haas has identified. First of all, epistemic communities have a “shared set of normative and principled beliefs which provide a value-based rationale for the social action of community members
”. Secondly, epistemic communities display “shared causal beliefs which are derived from their analysis of practices leading or contributing to a central set of problems in their domain and which then serve as the basis for elucidating the multiple linkages between possible policy actions and desired outcomes
”. The third characteristic of epistemic communities are “shared notions of validity,
i.e., intersubjective, internally defined criteria for weighing and validating knowledge in the domain of their expertise”
; while according to the fourth criteria, an epistemic community is “a common policy enterprise—that is a set of common practices associated with a set of problems to which their professional competence is directed, presumably out of the conviction that human welfare will be enhanced as a consequence
Since C.P. Snow’s work The Two Cultures and the Scientific Revolution
spoke of the dichotomy between “science” and “humanities”, the paradigms of different scientific cultures have been analyzed more closely [18
]. With regard to the discourses in the philosophy of science that have emerged following Snow’s analysis, P. Feyerabend’s “anything goes” could be mentioned here as an example [19
]. Ultimately, these postmodern analytical considerations lead to the discussion of the social relevance of science in general. Here, too, we would only like to refer to the discussion initiated by S. Funtowicz and J. Ravetz regarding the concept of “post normal science” [20
With these developments in the theory of science, the re-evaluations of the meaning of epistemic landscapes can at least be represented in a rudimentary way. Particularly, research dealing with the consequences of anthropogenic climate change is also called “problem driven science” [21
]. Not least because of this assessment, the hypothesis arises logically, according to which this research should precisely show a higher “interweaving” of classical epistemic landscapes. The present scientometric study attempts to test this hypothesis.
Problem-specific and solution-oriented research activities of epistemic communities such as public health, architecture, and urban planning can be better understood within this framework. Despite addressing the effects of climate change from different disciplinary backgrounds and with different epistemic practices, the normative guiding principles and the professional ethos of the various disciplines are very similar. They also share the intention to provide new knowledge and suggest potential policies or measures in order to improve human health and well-being. Research on the effects of climate change is not isolated from existing policy environments. They are in fact embedded within a dynamic and evolving political landscape, which requires constant knowledge transfer between scientific and political worlds. One of the main challenges is the knowledge transfer from scientific evidence of climate change impacts on human health and its implementation into mitigation and adaptation policies. In order for this to work, an engagement process between different actors is necessary. This allows the involved actors to develop a certain degree of ownership, which consequently increases the successful policy implementation [22
Our study intends to facilitate this process by providing a systematic bird’s eye view on the epistemic landscapes on climate change, health, and blue and green infrastructure by means of citation and keyword network analysis. Scientific documents constitute the common knowledge base of an epistemic community. Besides expressing a shared set of normative and causal beliefs, they also represent the common policy enterprise of the related epistemic community. Research articles furthermore provide a variety of additional data which can be used to analyze the development of research fields, the emergence of ideas, themes, and institutions, and the socio-epistemic structure of knowledge [23
]. By applying scientometric methods based on the principles of network analysis, this data can be used to explore the epistemic landscape of blue and green infrastructure in scientific discourses. In this way we want to shed light on different disciplinary embeddings, the interrelations between them, and their historical dynamics.
Scientometrics is defined as the application of different statistical, mathematical, and algorithmic methods to bibliographic data [24
]. The mapping and visualization of bibliographic data is part of scientometrics. It is used to visually explore the data and develop reasoning upon them. The bibliographic data used in this study is derived from SCOPUS and consists of information from peer reviewed documents (articles and reviews). These documents underwent a quality check by the respective epistemic community in a highly formalized process. According to Haas, this refers to the third criteria of epistemic communities, which involves the publication of studies based on established scientific practice, journal submission routines, editor selection standards, review procedures, including potential revision or refinement of manuscripts, and publishing these as articles accessible to the scientific community [17
]. These documents can be conceptualized as knowledge artefacts. Their analysis with scientometric methods sheds light on the structure of the overall knowledge repository within a respective scientific field and its corresponding epistemic community. In this understanding, the bibliographic data are standardized and codified information on knowledge artefacts.
We utilize mapping and clustering techniques provided by the VOSviewer tool to analyze and study the created networks based on bibliographic data [25
]. The analysis of scientific literature networks is a widely applied method in scientometrics to identify emerging topics and research fields of scientific domains [26
]. It can also be used to analyze the historical developments of topics and research fields, thus allowing insights into the historically evolved structure of research related networks [30
]. The aim of our study is to provide insights into the epistemic landscapes dealing with climate change-induced health effects and possible technological and nature-based interventions to cope with these. Our guiding research questions are:
What is the structure and what are the main topics of the epistemic landscape on climate change induced health effects and urban blue and green infrastructure?
What inter-connections can be identified between different disciplines (e.g., urban planning, architecture and public health, medicine) concerning the emerging health burden induced by climate change for urban settlements?
What implications can be derived from the results for underlying research activities and policy making?
We mapped networks based on bibliographic data retrieved from documents in SCOPUS. We used this data to create a keyword co-occurrence network and a citation network. The keyword co-occurrence network was used to gain insights into the topics and their underlying evolutionary dynamics. The citation network was used as a proxy to identify epistemic communities producing and using these documents and their interrelations. Mapping and clustering procedures incorporated in VOSviewer were applied in order to provide insights into the structure of the epistemic landscapes (i.e., networks). These clustering algorithms create a two-dimensional map in which the nodes with high association strengths have a shorter distance to each other. In VOSviewer this shorter distance is an indication for the relatedness of the nodes. This leads to areas in the overall network that are denser than others (clusters). The mathematical foundations for the clustering algorithms in VOSviewer are described in detail in Waltman, van Eck, and Noyons [30
]. However, a variety of different clustering methodologies exist, as this is a highly dynamic field of research in scientometrics [31
]. Thus, the application of different clustering techniques to the same dataset may yield different clustering results. As VOSviewer is a commonly used tool for scientometrics and furthermore is constantly updated by its developers, we decided to choose it for this study.
However, the study not only relies on quantitative results produced by VOSviewer. These results allowed us to identify central documents and topics by means of centrality-based network measures (citations, occurrences, co-occurrences). In the next step, the identified documents and topics were used as a starting point for a more in depth qualitative analysis. In contrast to other scientometric studies, the combination of quantitative and qualitative analysis allowed us to gain more in-depth insight. Besides that, the authors of this article have dedicated expertise concerning the topics of urban green infrastructure, health, urban planning, and sustainability sciences. This expertise was used not only to validate the results but also to widen the scope of the discussion. The validation of bibliometric networks by experts is something that is neglected too often, although it is a very important aspect, as highlighted by Noyons [32
2.1. Keyword Co-Occurrence Networks
Keyword co-occurrences are an important type of relational bibliographic data as they contextualize different documents according to their thematic content. Keywords are not always restricted to individual words. Usually, they contain multiple words or key terms. For example, if in two documents the keywords “climate-change” and “heat stress” appear in the keyword section, then these two documents are related to each other and the two keywords are connected by a relation with the value 2, because the keywords co-occur in 2 documents [25
]. In keyword co-occurrence networks, the size of the nodes reflects the number of their occurrences. This is an indication of the overall relevance of the respective keyword in the dataset. As keywords represent the content of a document in the most condensed form possible, a network of co-occurring keywords indicates the thematic landscape. We used the constructed keyword co-occurrence map in combination with a qualitative review of central documents to identify the research themes represented within the bibliographic dataset.
We first identified central and interconnected keywords in the network, based on their occurrences and co-occurrences. In the second step, we used this information in combination with a reference manager to retrieve the documents from which they were drawn. This reverse engineering process allowed us to embed the identified central and interconnected keywords in their initial document context (prototypical or representative documents). These documents were qualitatively analyzed in order to obtain an understanding of the underlying topics. It furthermore enabled us to investigate the thematic structure of the research fields and to identify major research topics and trends within scientific domains [34
]. Prior to creating the term co-occurrence maps with VOSviewer, a terminological thesaurus was constructed, based on certain standards [35
]. Words may have different spelling or common stems but different variations in terms of affixes (or associated words). Furthermore, there is a high level of variation concerning words and concepts used to describe the same phenomena (i.e., synonymous expressions). In such cases, words were merged under the same conceptual umbrella in order to generate a more reliable co-occurrence map.
2.2. Citation Networks
Citations are another important type of relational bibliographic data as they contextualize different documents across a temporal dimension. The citations authors make are regarded to be the branches of their intellectual pedigree. Thus, citation networks have a temporal dimension—meaning that a citation can only refer to a (cited) document, which is older than the citing document. A citation network is a representation of the citations that occur between the documents, and it thus relates them to each other. Two documents are connected if a citation has occurred between them. We utilized citation networks in order to identify document-based epistemic communities (i.e., publication clusters) and the relatedness of these communities to each other.
Besides that, citations represent a formalized and codified form of communication, which allows researchers to be more precise in their argumentation [37
]. Citations also have the potential to connect different, otherwise isolated, epistemic communities. This may be especially relevant for interdisciplinary work as different knowledge bases and epistemic practices are connected through citations [23
]. Citations can also be used to assess the scientific importance of a document. In general, articles with a higher number of citations are more visible within a certain research field and thus are often perceived to be more important. The authors of a research article refer to theories, results, and conclusions of former works and use them as a frame of reference in their own publication.
A frame of reference can have different qualities. In some cases, it is attesting (i.e., supporting the cited work) in other cases it is objecting (i.e., not supporting the cited work). Therefore, citations are a valuable resource for the analysis of the scientific development paths and epistemic communities [39
]. The citation network analysis of collected bibliographic data is central to our study. The citation network served to identify key publications within the collected bibliographic dataset (in terms of citations), groups of articles that are linked by citations (clusters), and articles that act as a bridge between different scientific subfields.
Keyword co-occurrence and citation analysis were performed to review and map the literature landscape related to climate change-induced health effects and possible technological and nature-based interventions to cope with these. Further methodological details of the VOSviewer layout and clustering techniques can be found in Van Eck, Waltman, Dekker and van den Berg [40
] Waltman, van Eck and Noyons [30
], Waltman and Van Eck [41
], and Van Eck and Waltman [42
2.3. Search Strategy and Search Query Definition
A well-known challenge in any study involving scientometric methods is the collection of relevant data with a predefined search query. The development of the search query is an iterative process, in which the retrieved results are constantly checked for their relevance. Thus, it takes time to identify unambiguous and relevant search terms and to combine them in a meaningful way. The search query needs to represent and describe the research field in such a way that the results of the search produce a bibliographic literature corpus with a high degree of completeness, ensuring that relevant literature is covered by the search query whereas non-relevant literature (“noise”) is reduced to a minimum.
The final search query consisted of different components. Each of these components has specific functions for the identification of relevant literature. The search query for SCOPUS consisted of three different components:
COMP_CC: Component consisting of terms related to climate change issues (e.g., urban heat island, climate change, urban sustainability, etc.);
COMP_HE: Component consisting of terms related to health effects (e.g., heat stress, cardiovascular, etc.);
COMP_UGI: Component consisting of terms related to mitigation and adaptation strategies and technological and nature-based interventions with urban green and blue infrastructure (e.g., green roofing, green facading, street greenery, etc.).
The search components aimed to retrieve documents on these three topics (Table 1
). The search components were combined with each other in order to reflect all possible thematic contexts. A combination of COMP_CC with COMP_UGI retrieved relevant documents dealing with health-related aspects and urban blue and green infrastructure interventions. Similarly, the combination of the COMP_UGI with COMP_CC captured documents providing insights into urban blue and green infrastructure interventions in the context of climate change. In total, four searches were performed (COMP_CC+COMP_HE+COMP_UGI/COMP_CC+COMP_HE/COMP_HE+COMP_UGI/COMP_CC+COMP_UGI). The results of all possible combinations of the three search term components were merged into one bibliographic dataset. The search query was directed towards the title, abstract, and keywords of the respective documents. However, the search performed with the combination COMP_CC+COMP_HE was restricted to only provide results if the defined search phrases were present in the title of the documents, otherwise the search phrase would have retrieved a very high amount of false positive documents. The manual relevance screening of the documents would not have been possible in this case.
Further limiting conditions of the search strategy concern the time period (1990–2020) and the document types, i.e., only research articles and reviews were collected. The broad time frame reflects the historical development of climate change discourse and the debate of its potential implications for health emerging in the 1990s (UNFCC signed in 1992 by 154 states). The year 2020 was defined as upper limit. Restricting the search query to articles and reviews ensured consistency of bibliographic data. Contrary to book chapters and conference proceedings, scientific articles and reviews are more consistent (e.g., more complete data, dedicated reference lists, etc.). Language was limited to English. Data gathering and screening were finalized on 1 September 2021.
2.4. Relevance Screening
Although the search query was developed iteratively, still some false positives (i.e., not relevant articles or reviews) were part of the search results using SCOPUS. Therefore, a qualitative relevance screening evaluated titles and abstracts in a second step. The criteria applied were that an article should either reflect on the direct and indirect climate change induced health effects or on technical and/or nature-based interventions (urban green or blue infrastructure) in view of coping with climate change effects. The screening process also served as validation. The number of false positives was <5% of the total number of results retrieved. False positives were removed from the dataset.
Climate change poses a broad variety of systemic risks for human health, well-being, and the living environment in general. With increasing urgency of counteraction, different adaptation and mitigation measures to cope with climate change-induced health risks are becoming increasingly relevant. These measures, however, must take into account a high degree of complexity. In light of ageing societies, effects may even become more severe as the vulnerable population groups increase [15
]. Temperature rise and resulting heat stress not only directly affect public health but also exert indirect effects by, e.g., reducing agricultural productivity [58
]. This feeds back on health and well-being due to a growing risk of malnutrition. Increasing heat stress also threatens overall economic productivity by reducing labor capacity during heat waves [59
]. Emerging infectious diseases as well as mental health issues add further complexity to the respective mechanisms [60
Nature-based solutions, e.g., urban blue and green infrastructure, have the potential to address several climate change induced health issues. They can positively influence the health and well-being of the urban population. Our findings show that several relevant topics emerged during the last 30 years and that they peaked at different times. The most recent topic refers to research targeting urban blue and green infrastructure as adaptation and mitigation measures. Ambient air temperature can be reduced by up to 4.0 °C through evapotranspiration [62
]. Additionally, extensive green roofs enhance natural rainfall retention capacity in urban areas by up to 22% [63
]. As extreme storm water events are becoming more probable because of climate change, urban sewage systems can easily be overburdened. This can paralyze cities on a large scale, causing not only economic damages but also human casualties. Urban vegetation also acts as a passive filter of urban air pollution. It has been shown that city greening can effectively filter airborne particulate matter, thus reducing adverse effects on health [64
]. Besides these physical benefits, urban vegetation contributes to mental health [68
However, existing knowledge on climate change effects and possible mitigation and adaptation measures is still fragmented across different disciplines. Our results indicate that the citation based “interaction” between documents related to health research (red and blue cluster in Figure 2
) and documents related to urban and landscape planning, civil engineering, or architecture (green cluster in Figure 2
) is relatively weak. The connection between these document-based epistemic communities is created via concern for the urban heat island effect and its implications on human health. In this context, nature-based interventions are discussed as potential solutions to cope with overheating.
We would have expected a tighter connection between these communities and disciplines. The benefits provided by urban blue and green infrastructure seem to perfectly fit in the causal relationship between climate change and health. Thus, it was surprising to see that the citation based “interaction” is not better developed so far. However, it is also necessary to remark that the academic discourse on urban blue and green infrastructure is the most recent part in the citation network. The “citation gap” between the left and right cluster in Figure 2
represents only the status quo. We may also interpret it as a condensation core for an increasing convergence between usually isolated disciplines (medicine related and urban planning and engineering related). At least this would be desirable as for a single discipline and epistemic community, it is nearly impossible to solve such a complex problem like climate change and its related health effects. Single disciplines can only provide pieces of potential solutions. Addressing complex societal problems demands contributions from a variety of disciplines and also must consider knowledge incorporated in and produced by non-scientific entities. Referencing across different epistemic communities and disciplinary boundaries indicates that research on urban greening is increasingly contextualized with medical and public health-related findings. Previously fragmented knowledge is thus put into broader context. In a recent scientometric study on climate change with a focus on infectious diseases, Sweileh showed that research activities on the health effects of climate change have been sharply increasing since 2007, but that innovations, policies. and the preparedness of the health system still need to catch up [70
]. This finding points towards a shared responsibility of different actors and entities in view of tackling the problem. It furthermore shows that, although the knowledge exists, the operationalization of this knowledge in action lags behind. Literature shows that strong causal links between health, overheating, energy consumption, pollution, income, and vulnerability exist but that an integrative and holistic frame theorizing these causalities is still lacking. In order to address this shortcoming, a conceptually more extended and interdisciplinary framework is necessary [71
]. Adaptation and mitigation measures need to consider the complexity of underlying cause–effect relationships. Health actors need to be involved in the discussion on the built environment and vice versa. Frameworks developed by public health professionals already exist and may be of interest for this topic [72
Despite the emerging demand for interdisciplinary cooperation, and indications of a convergence of different disciplines addressing the same societal grand challenge, there are still gaps in research that need to be addressed properly. This includes more research on the interplay between climate change-adapted built environments and their effects and relation to health impacts [73
]. New and adequate funding regimes as well as policy strategies are necessary for progress in this regard. They would facilitate inter- and transdisciplinary research on the nexus between health, climate change, and nature-based interventions. In order to successfully address the challenges and public health burdens created by climate change, a coordinated and holistic approach is needed, which embraces a variety of knowledge bases across different disciplines and entities.
Currently, decisions on the built environment are usually made by city planners, politicians, investors, and public service officials. Considering a health-in-all-policies perspective, this is no longer sufficient. Public policies should be designed across sectors and need to systematically take into account their health and health systems implications [75
]. Because the built environment affects health and well-being, it is necessary to involve health professionals in respective decision-making processes [77
]. Moreover, coupling climate change mitigation policies in urban space with health care related policies may increase the legitimacy of measures within both policy fields since their ultimate outcomes will be beneficial for both human well-being and the effectiveness of climate change adaptation as well as mitigation [78
The underlying study also has limitations, which need to be pointed out. The first one is concerned with SCOPUS as a data source. Although SCOPUS is one of the largest scientific databases, including journals from a variety of disciplines, there are also journals that are not indexed in SCOPUS. This includes for instance sources of regional interest. Nevertheless, this also holds true for alternative databases such as Web of Science. Concerning the thematic coverage, SCOPUS is well positioned in areas like natural, medicine, and health sciences but also engineering and technology. Pranckutė [79
] has extensively analyzed and compared SCOPUS and Web of Science. In conclusion, SCOPUS performs better according to the criteria like implemented impact indicators, coverage, and usability.
Another limitation, which needs to be pointed out, is related to the search query. In addition, the best-defined search query cannot guarantee to cover 100% of the relevant literature (i.e., to be complete). The search query is always a compromise between noise and relevance. Furthermore, SCOPUS (as well as other databases) are not immune to errors that occur in publication metadata. Our relevance screening of the dataset intended to address the issues related to relevance and potential errors.
There is also a disadvantage concerning the application of direct citation data for the construction of citation networks. Citation data are dynamic bibliographic data, meaning that during the analysis of that data at a certain point in time, there may be some documents that have no relation (i.e., citation) with other documents. During the clustering procedure, this leads to the effect that these documents cannot be assigned to a cluster. However, direct citations have been shown to produce more accurate clusters compared to other citation-based network analyses like bibliographic coupling or co-citation [80
A further limitation is also related to the clustering procedures performed in VOSviewer. Within the research field of scientometrics, a broad variety of different clustering methodologies exists [31
]. The application of different clustering techniques to the same dataset may yield different results. However, VOSviewer is a broadly used, well maintained, and renowned tool for scientometric analysis yielding highly reproducible and high-quality results.
The results of this scientometric study show that a multidisciplinary reference to blue and green urban infrastructure and health can be traced in the scientific world. These discourses can be seen as an encouraging sign of the need for intra-scientific interdisciplinary exchange. Notwithstanding this, however, several areas remain to be mentioned into which this exchange of expertise must continue.
Complex societal problems, such as the question of how to deal with climate change, must be addressed as broadly as possible. This breadth must of course also be reflected in the scientific expertise that flows into general social discourse. Our results showed that in the academic world, technological and nature-based interventions as measures to cope with climate change-induced health effects in urban spaces is an emerging field of research. The disciplinary foundation of this emerging field of research is located within urban and landscape planning, civil engineering, and architecture. To our surprise, its relation to the “older” scientific discourse on health and medicine related research on climate change is not as strong as expected or as it should be. We think that this gap needs to be addressed by, e.g., implementing specific research funds that intend to build intellectual capacity at the disciplinary intersection between health and urban planning professionals. Additional communication channels between academia, policy making, and the society in general need to be implemented in order to not only achieve integrative and holistic policy making but also to raise awareness and to mobilize society. There is still plenty of untouched potential for collaboration and knowledge exchange between different actors, e.g., scientists, politicians, urban and transportation planners, healthcare providers, and concerned individuals and citizen groups. Here, broadly understood interdisciplinary scientific expertise can make a contribution to raising awareness of the problem among social actors. The sooner this goal is achieved, the better displacement mechanisms, e.g., in the sense of cognitive dissonance of individual actors, can be broken up. Finally, this improved awareness of the problem provides the indispensable basis for the development of mitigation strategies that are widely accepted by society. This observation is not only calling for new ways of thinking, e.g., acknowledging longer time frames than usual in political decision making, strengthening systems thinking approaches instead of assuming linear causalities, but it also requires effective risk communication and appropriate actions that lead to synergistic health, environment, economic, and social benefits.