Evidence map›Paper›PMID 42088353›Full record

ArticleiScience2026

Differentiated impacts of climate physical risks on the Indian power sector.

Abhinav Jindal, Ruben Kerkhofs, Gireesh Shrimali

Abstract read
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Abhinav JindalSenior Faculty, Power Management Institute, Noida, India.
Ruben KerkhofsStatistics and Risk, Department of Mathematics, KU Leuven, Leuven, Belgium.
Gireesh ShrimaliOxford Sustainable Finance Group, Smith School of Enterprise and the Environment, Oxford University, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As India faces decarbonization and climate hazards, analyzing financial implications of climate-related risks for power sector is critical. This study presents a forward-looking, location focused, technology-wise analysis of physical climate risks for Indian power companies using novel asset-level methodologies. To assess physical risks, particularly flood exposure, we use spatially explicit modeling across 424 power-generating assets representing over 90% of India's capacity. Monte Carlo simulations reveal that without protective infrastructure, average losses exceed 19%, with 99th percentile tail risks surpassing 24%. However, investment in 100-year flood protection reduces average losses to under 1% and tail risks to below 2%. Results show that the effectiveness of risk mitigation varies significantly by technology and geography, with coal and gas assets benefiting most from protective investments, and coastal regions like Kerala and Gujarat showing highest vulnerabilities. This study provides a comprehensive empirical quantification of physical climate risks for Indian power firms at asset levels.

Indexed as

energy engineeringenergy sustainabilityenergy systemsglobal change

Identifiers

PMID42088353
PMCPMC13137212

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.