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Updated: Apr 14, 2026

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Characterizing Critical Sources of Carbon Emissions Using Principal Component Analysis.

Moiz Qureshi1,2, Muhammad Ismail3, Muhammad Daniyal4

  • 1Department of Statistics, Quaid-i-Azam University, Islamabad, 45320, Pakistan, qau.edu.pk.

Thescientificworldjournal
|April 13, 2026
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Summary
This summary is machine-generated.

Principal component analysis (PCA) identified key drivers of carbon dioxide (CO2) emissions. Electricity production and industrial growth significantly impact CO2 levels, informing environmental policy.

Keywords:
carbon dioxide (CO2) emissionsenvironmental managementpolicy formulationprincipal component analysissustainable development

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Area of Science:

  • Environmental Science
  • Data Analysis
  • Sustainable Development

Background:

  • Rising carbon dioxide (CO2) emissions pose a significant threat to global sustainable and economic development.
  • Countries experiencing rapid population growth, industrialization, and high energy demands are particularly affected.

Purpose of the Study:

  • To evaluate the primary drivers of carbon emissions using Principal Component Analysis (PCA).
  • To identify the most significant factors contributing to CO2 emissions between 1960 and 2018.

Main Methods:

  • Utilized Principal Component Analysis (PCA) on data spanning from 1960 to 2018.
  • Analyzed eigenvalues and scree plots to determine dominant principal components.

Main Results:

  • Two principal components (C.1 and C.2) explained 77% of the total variance in carbon emissions.
  • C.1 strongly correlated with CO2 emissions, total population, and electric energy production.
  • C.2 showed a significant connection to industrial growth.

Conclusions:

  • PCA effectively distinguishes key drivers of carbon emissions, highlighting the interplay between electricity generation (especially coal) and demographic factors.
  • Findings provide insights for environmental management and policy development to mitigate CO2 emissions.