‘Debt cannot be the pathway to climate resilience'

Writing from Gurugram, India, sustainability researcher Nirbhay Rana argues that countries with the smallest historical carbon footprints are facing the most severe climate shocks, yet continue to receive inadequate and often counterproductive support.

Rana highlights the growing pressure on labour-intensive sectors such as cotton farming, weaving communities and garment manufacturing — all severely affected by extreme heat, erratic monsoons and worsening water shortages.

While these communities are asked to both decarbonise and adapt, he writes, meaningful assistance remains almost nonexistent, and what does arrive often takes the form of loans rather than equitable finance.

"The gap is not only financial — it is structural, rooted in unequal development," Rana says. "Treating climate finance as debt undermines the very idea of a just transition. Debt cannot be the pathway to climate resilience for the global South."

He calls for grant-based funding, accessible technologies and long-term partnerships that strengthen local capacity rather than burden countries already grappling with development challenges. India, he notes, is rapidly expanding renewable energy at a pace faster than many historic emitters during their own industrialisation.

"What we seek is not charity," he writes. "We seek fairness — in line with science, history and the Paris Agreement. Climate ambition must finally rest on climate justice."

A warning about skewed climate data and diminishing global knowledge

In a second letter, John Green reflects on recent commentary by George Monbiot and Deepak Varuvel Dennison, underscoring the dangers posed by the dominance of Western and English-language information in global datasets.

Green argues that AI systems, media outlets and climate analyses routinely marginalise local knowledge and non-Western expertise — distorting the global understanding of both climate change and broader geopolitical realities.

"Vital local experience and wisdom are being pushed to the margins," Green writes, "and this bias has serious consequences for how we perceive the world."

He warns that the expansion of AI could deepen this imbalance unless corrective action is taken, stressing the need for more inclusive, representative and globally sourced data.

"If we fail to recognise and correct this distortion," he notes, "we risk losing a meaningful concept of reality — and with it, our ability to make effective decisions."