Evidence map›Paper›PMID 40064986›Full record

ArticleScientific reports2025

Evaluating the environmental effects of bitcoin mining on energy and water use in the context of energy transition.

Radulescu Magdalena, Kamel Si Mohammed, Abdelmohsen A Nassani, Nicoleta Dascalu

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

4 authors.

Radulescu MagdalenaNational University of Science and Technology Politehnica Bucharest, Pitesti University Center, Pitesti, Romania. magdalena.radulescu@upb.ro.
Kamel Si MohammedUniversité de Lorraine, CEREFIGE, F-57000 Metz, France. kamal.si-mohammed@univ-lorraine.fr.
Abdelmohsen A NassaniDepartment of Management, College of Business Administration, King Saud University, Riyadh, Saudi Arabia.
Nicoleta DascaluNational University of Science and Technology Politehnica Bucharest, Pitesti University Center, Pitesti, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigates the impact of Bitcoin's energy and water consumption on environmental sustainability, focusing on the load capacity factor (LCF) and the roles of energy transition green technology in major cryptocurrency-producing nations. Utilizing the method of moments quantile regression (MMQR) approach, the findings reveal a negative impact of mining energy consumption on environmental sustainability, particularly in the lower quantiles, with a stronger negative effect in the higher quantiles. Energy transition plays a critical role in moderating this impact, though the shift towards cleaner energy sources has not been sufficient to mitigate the adverse environmental effects. The water footprint has limited influence on LCF across upper and lower quantiles. Moreover, the results do not support the LCF hypothesis. An increase in mining activity leads to a rise in LCF, while this effect turns negative in the 90th quantile. These findings underscore the importance of energy transition in reducing Bitcoin's environmental footprint and emphasize the need for policymakers to swiftly enact regulations and foster innovative technologies to promote environmentally sustainable digital currencies while providing valuable insights into water resource management.

Indexed as

Energy consumptionMiningMMQRSustainable developmentWater usage

Identifiers

PMID40064986
PMCPMC11894042

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.