A Systematic Investigation Of Climate Change Impacts And Disaster Risk Reduction Strategies Using Data-Driven Analytical Models

Authors

  • Dr. T. Megala
  • Dr.K. Srinivasan
  • Dr.K. Sathishkumar
  • Dr. M. Ramalingam
  • Dr.S. Pandikumar
  • Dr.A. Mummoorthy
  • R. Naveenkumar

Keywords:

Climate change, risk, energy, atmosphere, building, disaster, radiation, and mitigation

Abstract

Changes in climate could occur owing to both natural variability as well as human activity. Natural variability arises from the internal processes at work in the climate system and not from changes in external forces. Human induced climate change is also known as anthropogenic climate change. This is attributable to the increasing concentration of GHGs in the atmosphere which occurs as these gases, emanating from various human activities (e.g., burning of fossil fuels), are emitted into the atmosphere. The analysis in this article focuses mainly on public adaptation measures. Construction projections for the year 2050 across a number of uniform climate change scenarios are carried out for construction of building at the all-India level. Assuming that the magnitude of construction loss under climate change are of similar order of magnitude witnessed for all other buildings over the medium-term, the additional investments in the above productivity enhancement measures are calculated. The total cost of adaptation under various scenarios is estimated to range between US $ 1.1 - 4.3 billion per annum. The significantly low costs (< 1% of agricultural value added) associated with these public adaptation measures suggests the importance of adhering to a ‘no regrets’ path in tackling climate change, while ‘mainstreaming’ adaptation into the development policy agenda.

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Published

2026-06-14

How to Cite

Megala, D. T., Srinivasan, D., Sathishkumar, D., Ramalingam, D. M., Pandikumar, D., Mummoorthy, D., & Naveenkumar, R. (2026). A Systematic Investigation Of Climate Change Impacts And Disaster Risk Reduction Strategies Using Data-Driven Analytical Models. International Journal of Artificial Intelligence and Machine Learning, 6(5s), 252–262. Retrieved from https://www.svedbergopen.com/index.php/ijaiml/article/view/580