Identifying American climate change free riders and motivating sustainable behavior

Free riders, who benefit from collective efforts to mitigate climate change but do not actively contribute, play a key role in shaping behavioral climate action. Using a sample of 2096 registered American voters, we explore the discrepancy between two groups of free riders: cynics, who recognize the significance of environmental issues but do not adopt sustainable behaviors, and doubters, who neither recognize the significance nor engage in such actions. Through statistical analyses, we show these two groups are different. Doubters are predominantly male, younger, with lower income and education, exhibit stronger conspiracy beliefs, lower altruism, and limited environmental knowledge, are more likely to have voted for Trump and lean towards conservative ideology. Cynics are younger, religious, higher in socioeconomic status, environmentally informed, liberal-leaning, and less likely to support Trump. Our research provides insights on who could be most effectively persuaded to make climate-sensitive lifestyle changes and provides recommendations to prompt involvement in individual sustainability behaviors. Our findings suggest that for doubters, incentivizing sustainability through positive incentives, such as financial rewards, may be particularly effective. Conversely, for cynics, we argue that engaging them in more community-driven and social influence initiatives could effectively translate their passive beliefs into active participation.

Do fossil fuel firms reframe online climate and sustainability communication? A data-driven analysis

Identifying drivers of climate misinformation on social media is crucial to climate action. Misinformation comes in various forms; however, subtler strategies, such as emphasizing favorable interpretations of events or data or reframing conversations to fit preferred narratives, have received little attention. This data-driven paper examines online climate and sustainability communication behavior over 7 years (2014-2021) across three influential stakeholder groups consisting of eight fossil fuel firms (industry), 14 non-governmental organizations (NGOs), and eight inter-governmental organizations (IGOs). We examine historical Twitter interaction data (n = 668,826) using machine learning-driven joint-sentiment topic modeling and vector autoregression to measure online interactions and influences amongst these groups. We report three key findings. First, we find that the stakeholders in our sample are responsive to one another online, especially over topics in their respective areas of domain expertise. Second, the industry is more likely to respond to IGOs' and NGOs' online messaging changes, especially regarding environmental justice and climate action topics. The fossil fuel industry is more likely to discuss public relations, advertising, and corporate sustainability topics. Third, we find that climate change-driven extreme weather events and stock market performance do not significantly affect the patterns of communication among these firms and organizations. In conclusion, we provide a data-driven foundation for understanding the influence of powerful stakeholder groups on shaping the online climate and sustainability information ecosystem around climate change.

Remote control of mechanochemical reactions under physiological conditions using biocompatible focused ultrasound

External control of chemical reactions in biological settings with spatial and temporal precision is a grand challenge for noninvasive diagnostic and therapeutic applications. While light is a conventional stimulus for remote chemical activation, its penetration is severely attenuated in tissues, which limits biological applicability. On the other hand, ultrasound is a biocompatible remote energy source that is highly penetrant and offers a wide range of functional tunability. Coupling ultrasound to the activation of specific chemical reactions under physiological conditions, however, remains a challenge. Here, we describe a synergistic platform that couples the selective mechanochemical activation of mechanophore-functionalized polymers with biocompatible focused ultrasound (FUS) by leveraging pressure-sensitive gas vesicles (GVs) as acousto-mechanical transducers. The power of this approach is illustrated through the mechanically triggered release of covalently bound fluorogenic and therapeutic cargo molecules from polymers containing a masked 2-furylcarbinol mechanophore. Molecular release occurs selectively in the presence of GVs upon exposure to FUS under physiological conditions. These results showcase the viability of this system for enabling remote control of specific mechanochemical reactions with spatiotemporal precision in biologically relevant settings and demonstrate the translational potential of polymer mechanochemistry.