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 ( = 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.
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http://dx.doi.org/10.1038/s44168-023-00086-x | DOI Listing |
Nat Commun
January 2025
Center for Global Sustainability, University of Maryland, College Park, MD, USA.
In 2025, countries are expected to submit a third round of nationally determined contributions (NDCs) that outline emission reduction goals for 2035. These new NDCs will be important for global alignment with the Paris Agreement's long-term goals. Setting an ambitious and plausible 2035 NDC in the United States (US) could be crucial in motivating high levels of ambition globally.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
Science and Technology Branch, Pacific Environmental Science Centre, Environment and Climate Change Canada, Pacific and Yukon Laboratory for Environmental Testing, North Vancouver, BC, Canada.
Spilled plant-based oils behave very differently in comparison to petroleum oils and require different clean-up measures. They do not evaporate, disperse, dissolve, or emulsify to a significant degree but can polymerize and form an impermeable cap on sediment, smothering benthic media and resulting in an immediate impact on the wildlife community. The current study explored the application of rapid up-to-date direct analysis in real time (DART) with high-resolution mass spectrometry for plant-based oil typing.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
China Three Gorges Corporation, Beijing 100038, China.
With the rapid decline in the levelized cost, offshore wind power offers a new option for the clean energy transition of the power sector in China's coastal areas. Here, we develop a power system capacity expansion and operation optimization model to simulate the penetration of offshore wind power in China and quantify the associated health effects. We find that offshore wind power has great potential in mitigating the negative impacts of existing coal-fired power emissions.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
State Key Laboratory of Marine Resources Utilization in South China Sea, School of Marine Science and Engineering, Hainan University, Haikou 570228, China.
In response to the 2023 "Action Plan for Methane Emission Control" in China, which mandates precise methane (CH) emission accounting, we developed a dynamic model to estimate CH emissions from fossil-fuel and food systems in China for the period 1990-2020. We also analyzed their socioeconomic drivers through the Logarithmic Mean Divisia Index (LMDI) model. Our analysis revealed an accelerated emission increase (850.
View Article and Find Full Text PDFiScience
January 2025
Pacific Northwest National Laboratory, Joint Global Change Research Institute, 5825 University Research Court, Suite 3500, College Park, MD 3500, USA.
In this paper we contribute to a long history of research studying interactions between energy systems, international energy trade, and macroeconomic activity. We develop and employ methods to quantify transmission pathways for energy markets to affect the macroeconomy and CO emissions. We track the long-term consequences of a hypothetical permanent disruption to global energy markets, cession of Russian fossil fuel exports, for energy markets, regional and global economic activity (gross domestic product [GDP]), labor and capital markets, and CO emissions against two dramatically different reference scenarios.
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