Modeling Earth Systems and Environment

, Volume 4, Issue 1, pp 339–348 | Cite as

Causal dynamics of CO2 source emissions and population in India using Bayesian approach

  • Sakshi Babbar
  • Richa Babbar
Original Article


The present study was undertaken to model causal relationship between several sources contributing to CO2 emission and population growth in India using a Bayesian approach. The data were collected from an International database. The Bayesian model was developed and evaluated using evaluation metrics, and the results were found to be promising. Based on probabilistic learning, it was found that with the increase in population, there is a higher probability that gas fuel and liquid fuel-based emissions will go higher, followed by solid fuel-based emission in order of decreasing probability. The sensitivity analysis confirmed strong influence of population growth on liquid fuel-based emissions. The study reveals the potential of a probabilistic study in identifying the sources that can be given due consideration for the purpose of managing CO2 emissions.


Global warming Fossil fuels Bayesian network k-means clustering Incremental association algorithm Sensitivity analysis 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of EngineeringGD Goenka UniversityGurgaonIndia
  2. 2.Department of Civil EngineeringThapar Institute of Engineering and TechnologyPatialaIndia

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