Chad M. Baum
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chadmbaum.bsky.social
Chad M. Baum
@chadmbaum.bsky.social
2.8K followers 1.1K following 190 posts
Assistant Professor @AarhusUni | Researcher of Public Perceptions of Climate Technologies | Carbon Dioxide Removal | Food + Agriculture | Geoengineering | Environmental Justice | All views my own
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chadmbaum.bsky.social
Happy to announce I have joined the Editorial Board at Energy Research and Social Science! 🌍💡

#ERSS has long been one of my favorite journals, and I thank @sovacool.bsky.social et al. for the opportunity.

I look forward to seeing your best articles soon 👇

www.sciencedirect.com/journal/ener...
September 17, 2025 at 7:41 AM
chadmbaum.bsky.social
Majority of African citizens (i) have not heard of climate change and (ii) place main responsibility for climate action on own governments or ordinary citizens-not historical emitters.

Data from Afrobarometer (2021-23), N=53,444, in 39 countries

🔗https://www.nature.com/articles/s43247-025-02244-x
April 28, 2025 at 8:18 AM
chadmbaum.bsky.social
The old site really has become a cesspool.

I happened to see that this is one of the more shared tweets that links to our new article 🗣️💩 Trafficking in blatant climate denial, masquerading as scientific independence.

Much happier to be over here! 💙🌈
March 20, 2025 at 4:05 PM
chadmbaum.bsky.social
🎉 Nature Communications Top 25 Social Science & Human Behavior Articles of 2024 Award

🧞Our #GENIE article examining #public perceptions and support of #CDR and #SRM across the global North and global South was one of the most-read in 2024!

🔗 www.nature.com/articles/s41...
@liviafritz.bsky.social
March 20, 2025 at 8:36 AM
chadmbaum.bsky.social
For further research, these findings invoke the need to deeply explore cultural differences in the importance or meaning of emotions (e.g. what it means to "hope"?).

As ever, this is a caution against research focused on a minimal subset of western countries - as a stand-in for the wider world 10/
Greenpeace activists display a big banner reading “We still have hope, Climate action now!” during an activity prior to a press conference of the Intergovernmental Panel for Climate Change (IPCC) at Songdo Convensia in Incheon on October 8, 2018. JUNG YEON-JE/Getty Images
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
The results provide the first global-level evidence of the relationship between discrete climate emotions and support of the various types of climate interventions.

What is revealed is the different roles and tendencies of the emotions vis-a-vis support for climate interventions 9/
F I G U R E 4 Visualizing the complexity of climate emotions and public support for climate intervention technologies. Source: Authors, based onSections 3.1–3.4.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
In contrast, being sad or angry was mostly relevant for more familiar, ecosystems-based #CDR such as afforestation or soil carbon sequestration 🌳🚜

Those who were sadder were more supportive of these options, whereas those who were angrier were less supportive 8/
TABLE 2 Standardized coefficient estimates for climate emotions vis-à-vis support for 10 climate-intervention options. Note: “+”reflects coefficient estimates significant at a level of p < 0.10. Responses to the dependent variable (technology support) on a five-point scale (1 = strictly reject, 3 = neither reject nor support, 5 = fully support, with “don’t know” option) were combined into a single factor for the three items on support. Multiple linear regressions also included the set of covariates (and intercept). Bold font indicates that an effect is significant (p < 0.05). Positively significant effects shaded in blue; negatively significant effects in orange. Abbreviation: BECCS, bioenergy with carbon capture and storage.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
Climate emotions are also linked to support of strategies for climate change 🎓⛏️

Being hopeful or worried were significantly (positively) related to support of climate interventions. This was true for solar #geoengineering and novel #CDR, such as direct air capture and enhanced rock weathering 7/
TABLE 2 Standardized coefficient estimates for climate emotions vis-à-vis support for 10 climate-intervention options. Note: “+”reflects coefficient estimates significant at a level of p < 0.10. Responses to the dependent variable (technology support) on a five-point scale (1 = strictly reject, 3 = neither reject nor support, 5 = fully support, with “don’t know” option) were combined into a single factor for the three items on support. Multiple linear regressions also included the set of covariates (and intercept). Bold font indicates that an effect is significant (p < 0.05). Positively significant effects shaded in blue; negatively significant effects in orange. Abbreviation: BECCS, bioenergy with carbon capture and storage.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
The fact that those in developing economies in global South were both hopeful and worried about climate change is intriguing.

Two countries (Nigeria, Saudi Arabia) were even on average more hopeful than worried.

This highlights under-appreciated role of hope in conversations on climate change 6/
Ranking of climate emotions across countries - for being hopeful and being worried about climate change.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
Hopefulness about climate change differed the most 🙏

Respondents in the developing economies were much more hopeful about climate change. Those in advanced economies in global North by far the least 5/
Table 1 Significant differences (p < 0.05) in climate emotions among country cohorts. Standard deviations are in parentheses. Note: Responses for “Hopeful,” “Afraid,” “Angry,” and “Sad” on a 1–5 scale (1 = not at all, 5 = extremely) to the question “How much do you feel each of these emotions whenthinking about climate change?”. Ordering of items was randomized. Responses for “Worried” on a 1–5 scale (1 = not at all worried, 5 = extremely worried) to the question “Howworried, if at all, are you about climate change, sometimes referred to as ‘global warming’?”. Individuals could also select “don’t know”; this was coded as missing data. Differentletters denote significant pairwise differences (p < 0.05) between the country cohorts for a given emotion, according to independent-samples Kruskal–Wallis H test analysis, with significance valued adjusted by Bonferroni correction for multiple comparisons.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
Those in BASIC/emerging economies (eg China, India, Brazil, Saudi Arabia) were angrier, sadder, and more afraid than elsewhere 😠☹️😱

For some emotions (sadness, anger), differences were minimal between developing economies in global South (Nigeria, Kenya, Dominican Republic) and advanced economies 4/
Table 1 Significant differences (p < 0.05) in climate emotions among country cohorts. Standard deviations are in parentheses. Note: Responses for “Hopeful,” “Afraid,” “Angry,” and “Sad” on a 1–5 scale (1 = not at all, 5 = extremely) to the question “How much do you feel each of these emotions whenthinking about climate change?”. Ordering of items was randomized. Responses for “Worried” on a 1–5 scale (1 = not at all worried, 5 = extremely worried) to the question “Howworried, if at all, are you about climate change, sometimes referred to as ‘global warming’?”. Individuals could also select “don’t know”; this was coded as missing data. Differentletters denote significant pairwise differences (p < 0.05) between the country cohorts for a given emotion, according to independent-samples Kruskal–Wallis H test analysis, with significance valued adjusted by Bonferroni correction for multiple comparisons.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
We identified significant differences in emotions by level of development (i.e. developing, emerging, advanced).

Worry was the most commonly expressed emotion🙍though this emotion was less prominent in advanced economies in the global North 3/
Table 1 Significant differences (p < 0.05) in climate emotions among country cohorts. Standard deviations are in parentheses. Note: Responses for “Hopeful,” “Afraid,” “Angry,” and “Sad” on a 1–5 scale (1 = not at all, 5 = extremely) to the question “How much do you feel each of these emotions whenthinking about climate change?”. Ordering of items was randomized. Responses for “Worried” on a 1–5 scale (1 = not at all worried, 5 = extremely worried) to the question “Howworried, if at all, are you about climate change, sometimes referred to as ‘global warming’?”. Individuals could also select “don’t know”; this was coded as missing data. Differentletters denote significant pairwise differences (p < 0.05) between the country cohorts for a given emotion, according to independent-samples Kruskal–Wallis H test analysis, with significance valued adjusted by Bonferroni correction for multiple comparisons.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
We employed a unique, global 🌍 dataset with 30,284 participants across 30 countries (in 19 languages 🗣️) to map the incidence of fear, hope, anger, sadness, and worry across countries 🙏🫦😩

The is first time the climate emotions of adults have been investigated on this scale 2/
F I G U R E 1 Geographic representation of 30 countries surveyed on climate-intervention technologies. Nationally representative surveys of supportfor climate intervention in 30 countries and 19 languages (at least 1000 participants in each). Samples representative in terms of age (between 18 and 74),gender, and geographic region, and with broad quotas (equal split above and below median) for education and income; Source: Authors.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
New #GENIE article on #climate emotions at a global level, and how these correspond to support for ten climate intervention approaches. Now available in Risk Analysis (with @liviafritz.bsky.social, Elina Brutschin, Benjamin Sovacool) 🧵

Open access link: onlinelibrary.wiley.com/doi/10.1111/...
F I G U R E 3 Emotions about climate change (hopeful, afraid, angry, and sad) across 30 countries, on a 1–5 scale (1 = not at all, 5 = extremely) withN = 30,284 participants (at least 1000 participants in each country); Numbers to the left reflect those answering “1” or “2,” in the middle “3,” and to the right“4” or “5.” Panel (a) shows the results for “hopeful”; Panel (b) for “afraid”; Panel (c) for ”angry”; and Panel (d) for “sad”.
March 17, 2025 at 10:56 AM
chadmbaum.bsky.social
Having to give a lecture today on "greenwashing" on short notice. Excellent reminder of amount of fascinating, necessary work on this topic, including by @desmog.bsky.social and @emorwee.bsky.social

Fantastic example on links between Ad/PR industry and fossil fuels: www.desmog.com/2025/02/10/a...
February 20, 2025 at 9:26 AM
chadmbaum.bsky.social
Global public perceptions on #climate change and carbon-dioxide removal #CDR and solar #geoengineering

The full #GENIE survey dataset (30 countries, 19 languages) is now available, open access, via the Knowledge Hub.

Please dig in! 🔬

cdr.apps.ece.iiasa.ac.at/story/2025_0...
February 6, 2025 at 9:12 AM
chadmbaum.bsky.social
More fundamentally, these insights shed light on prospective initiatives for the #emergence of #interdisciplinary knowledge areas (IKAs) more broadly, e.g., what is needed to build #legitimacy and how to better promote broad-based #collaboration 4/
Fig. 5. Go-zone chart showing importance and changeability ratings for the 55 statements. Remark: The four sectors are constructed using the average x- and y-values. Table 4. “Go-zone” of all statements above average in importance and changeability. These represent the key initiatives identified by actors in general as important for ecosystem emergence.
February 5, 2025 at 10:47 AM
chadmbaum.bsky.social
The collected insights from different actors comprising this ecosystem allowed us to first identify the drivers that are seen as most important and changeable for the emergence of #syntheticbiology.

We could also trace how different actors varied in their perceptions of key drivers 3/
Fig. 3. Pattern match based on importance ratings for the emergence of synthetic life sciences. Remark: Relationships between actors' ratings of the relative importance of ideas averaged across clusters presented.
February 5, 2025 at 10:47 AM
chadmbaum.bsky.social
We focused our attention on #universities as a key locus of knowledge creation and exchange - which we call #interdisciplinary invention #ecosystems 🎓

Through this lens, we engaged with N=49 actors from academia and industry in the ecosystem around a German university in North-Rhine Westphalia. 2/
Fig. 2. Cluster map based on importance of drivers for the emergence of synthetic life sciences. Note: Map shows 55 statements grouped into eight clusters (average ratings in parentheses). Ratings on a 5-point scale, with ratings from 1 to 3 indicating a statement (or cluster) is deemed relatively unimportant.
February 5, 2025 at 10:47 AM
chadmbaum.bsky.social
We also used multilevel linear regression analysis (with mixed effects and random slopes) to calculate the level of #trust at country level for five different types of actors.

#Trust in scientists/universities is consistently high ⚛️

Trust in national governments diverges significantly ⁉️5/
Fig. 2. Average predicted values of trust in different types of actors across countries. Note: Respondents were asked to indicate on a scale ranging from 1, “no trust”, to 6, “very high trust”, their level of trust in five types of actors “when it comes to their responsibility [and ability] to use these technologies (CDR/SRM) to limit the effects of climate change”. The order in which participants were asked to express their trust in each of the institutions was randomized. The figure is based on mixed effects multilevel linear regressions included in the SI. Y-axis based on the original scale of trust. X-axis ordered according to the average predicted value across the five types of actors for each country.
January 27, 2025 at 11:03 AM
chadmbaum.bsky.social
We also performed multilevel linear regression analysis w/ country-level fixed effects to identify individual-level determinants of trust in scientific institutions.

Key factors include: education (⬆️trust); liberal political views (⬆️); religiosity (⬆️); and living in large city (⬆️) 4/
Fig. 1. Predicted value of trust in universities and scientific research institutions across socio-demographic characteristics. Note: Respondents were asked to indicate on a scale ranging from 1, “no trust”, to 6, “very high trust”, their level of trust in five types of actors “when it comes to their responsibility [and ability] to use these technologies (CDR/SRM) to limit the effects of climate change”. The figure is based on a fixed effects multilevel linear regression included in the SI. X-axis based on the original scale of trust, from 1–6. Occupation color coded as such: grey for resource extraction sector, blue for blue-collar employments, green for sustainability and conservation sector, gold for high-prestige jobs, white for white-collar employments.
January 27, 2025 at 11:03 AM
chadmbaum.bsky.social
Publics see #experts serving many functions for #CDR and #SRM: communicator, advisor, decision-maker 🗣️

Of note, publics almost exclusively identify natural scientists and engineers🥼 as experts - NOT social scientists. Mention of non-scientific forms of expertise are minimal (but varies by tech) 3/
Table highlighting relevance of three strands of literature: (1) Roles of experts in decision-making, with a focus on climate; (2) Public perceptions of experts and trust in scientists, with a focus on climate; and (3) Trust in science and technology perceptions, with a focus on climate interventions
January 27, 2025 at 11:03 AM
chadmbaum.bsky.social
Using a mixed-methods dataset from 22 countries (N=22,222 survey, N=323 focus groups), we explore three questions related to #climate intervention:

(1) who publics see as an expert
(ii) envisioned roles of experts for governance
(iii) how (dis)trust in scientists unfolds in this context

2/
Fig. 3. Conceptual representation of key elements in public perceptions of experts in the governance of climate intervention technologies, including types of expertise, roles and ingredients for trustworthiness. Note: Distribution in the inner circle qualitatively reflects the unequal shares of mentions of social sciences as relevant expertise in the focus groups. The visualization does not imply strong relations or any directionality between elements across the three circles.
January 27, 2025 at 11:03 AM
chadmbaum.bsky.social
Exact odds ratios in Table below - interestingly, only two techs have positive impacts (#spillovers) across all dimensions. #DAC is one.

Other is enhanced weathering #ERW. Though its impacts for science and tech are not significant, likely because of small sample size (i.e. too little research) 5/N
Table showing exact odds ratios related to #CDR spillovers for all technologies, across all dimensions (science, technology, policy, media).
December 18, 2024 at 9:37 AM
chadmbaum.bsky.social
Direct air capture #DAC has stronger technological spillovers (i.e. patents).

Blue and #soil #carbon more impactful on policy.

Enhanced rock weathering #ERW dominant in traditional (and social) media, which is a very interesting finding 4/N
Radar maps showing impacts (for news media, citations, blog, policy, Facebook, Twitter, and patents) for CDR in general and eight specific technologies.
December 18, 2024 at 9:30 AM