Highlights The COVID-19 pandemic can be viewed as a rapid learning experiment about how to cope more effectively with climate change. Using insights into behavioral biases, we illustrate parallels between decisions about COVID-19 and climate change risks. Climate change risk can be mitigated by policies that work with, instead of against, an individual’s risk perceptions and biases. We conclude with recommendations for communication policies that make people pay attention to climate change risks. Government responses to the COVID-19 crisis should be linked with environmental sustainability and climate action.

European survey data shows strong temporal fluctuations in climate change concern within European countries and large differences in concern between these countries. However, there is as yet no comprehensive understanding of what drives these longitudinal and cross-sectional patterns. To fill this knowledge gap, this study analyzes data of over 155,000 survey respondents from 28 European countries over the period 2008-2017. This study is the first to apply within-between random effects models to simultaneously analyze longitudinal and cross-sectional determinants of climate change concern, and examine if and how the influence of these determinants has changed over time. Substantively, it researches the nexus between climate change and two other crises that have captured the imagination of European publics over the studied period: the liberal democracy crisis and the economic crisis. The former is characterized by the rise of right-wing populist parties in Europe. Right-wing populism is often at odds with climate change policies, and its rise in popularity could have undermined public concern about climate change. We find only a weak negative longitudinal relationship between such concern and the popularity of right-wing populist parties, and no significant cross-sectional relationship. We find that economic performance is strongly positively associated with concern, with GDP per capita being most important for explaining crosscountry differences in concern, and deviations in unemployment being most important for explaining longitudinal within-country change. However, this negative longitudinal relationship with unemployment weakens considerably over time, illustrating the importance of including dynamic effects in modeling efforts to generate more reliable results. Key policy insights. The percentage of European respondents mentioning climate change as one of the most serious world problems declined from 65% in 2008 to 43% in 2017.. This study does not find a strong direct relationship between the rise of climate skeptic right-wing populist parties and public concern about climate change.. Economic factors are important predictors of climate change concern, with GDP per capita being the dominant driver of between-country differences, and unemployment the dominant within-country predictor.. The marginal impact of unemployment was much stronger during, rather than after, the economic crisis.

Sea‐level rise (SLR) threatens millions of people living in coastal areas through permanent inundation and other SLR‐related hazards. Migration is one way for people to adapt to these coastal changes, but presents an enormous policy challenge given the number of people affected. Knowledge about the relationship between SLR‐related hazards and migration is therefore important to allow for anticipatory policymaking. In recent years, an increasing number of empirical studies have investigated, using survey or census data, how SLR‐related hazards including flooding, salinization, and erosion together with non‐environmental factors influence migration behavior. In this article, we provide a systematic literature review of this empirical work. Our review findings indicate that flooding is not necessarily associated with increased migration. Severe flood events even tend to decrease long‐term migration in developing countries, although more research is needed to better understand the underpinnings of this finding. Salinization and erosion do generally lead to migration, but the number of studies is sparse. Several non‐environmental factors including wealth and place attachment influence migration alongside SLR‐related hazards. Based on the review, we propose a research agenda by outlining knowledge gaps and promising avenues for future research on this topic. Promising research avenues include using behavioral experiments to investigate migration behavior under future SLR scenarios, studying migration among other adaptation strategies, and complementing empirical research with dynamic migration modeling. We conclude that more empirical research on the SLR‐migration nexus is needed to properly understand and anticipate the complex dynamics of migration under SLR, and to design adequate policy responses. This article is categorized under: Climate Economics < Aggregation Techniques for Impacts and Mitigation Costs Vulnerability and Adaptation to Climate Change < Learning from Cases and Analogies Assessing Impacts of Climate Change < Evaluating Future Impacts of Climate Change

This study adds to an emerging literature on the factors associated with individual perceptions of COVID-19 risks and decision-making processes related to prevention behaviors. We conducted a survey in the Netherlands (N = 3600) in June-July 2020 when the first peak of COVID-19 infections, hospitalizations, and deaths had passed, and lockdown measures had been eased. Dutch policies relied heavily on individual prevention behaviors to mitigate a second infection wave. We examine whether biases and heuristics that have been observed in how people perceive and respond to other risks also apply to the newly emergent risks posed by COVID-19. The results indicate that people simplify risk using threshold models and that risk perceptions are related with personal experiences with COVID-19 and experiences of close others, supporting the availability heuristic. We also observe that prevention behavior is more strongly associated with COVID-19 risk perceptions and feelings toward the risk than with local indicators of COVID-19 risks, and that prevention behavior is related with herding. Support for government lockdown measures is consistent with preferences that may contribute to the not-in-my-term-of-office bias. In addition, we offer insights into the role of trust, worry, and demographic characteristics in shaping perceptions of COVID-19 risks and how these factors relate with individual prevention behaviors and support for government prevention measures. We provide several lessons for the design of policies that limit COVID-19 risks, including risk communication strategies and appeals to social norms. Perhaps more importantly, our analysis allows for learning lessons to mitigate the risks of future pandemics.

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