Impact of Affluence, Population Growth and Technology on Environment in terms of CO2 Emission in Developing, Developed and Least Developed Economies
Bibliographic record
Abstract
Global warming is a tangible reality.Green House Gases (GHGs) are the main cause of this world-wide phenomenon.Since the middle of last century there has been an abrupt increase in GHG emission because of high anthropogenic pressure and fast economic growth in many parts of the world.Because of environmental concern all over the world there have been concerted efforts to cope up with this problem.Myriads of empirical studies were carried out and policy decisions were taken to contain CO 2 emission.This study is also undertaken to examine that which of the factors out of population growth, economic development and technological advancements cause more damage in terms of CO 2 emission.Then behavior of the most harmful factor is analyzed in Environmental-Kuznets -Curve to search a solution to this problem.This is accomplished through widely used models viz.IPAT model and Environmental -Kuznets -Curve (EKC).The impact on environment in terms of CO 2 emission is measured in 21 economies of the world comprising of seven in each three categories viz.developing, developed and least developed economies.The decompositionidentity of IPAT model is used in this study to identify the most harmful factor.It is found that the economic growth i.e.GDP per capita iscausing more damage to the environment in terms of CO 2 emission than population growth in developing and developed economies.However, in least developed economies technological factor is causing severe damage.It is because of the reason that poor countries are not in a position to adopt environmental friendly technologies particularly for energy production.The relationship of CO 2 emission and economic growth is then subjected to analysis in EKC.However, no ideal relation of inverted U shaped curve is found in any of the countries.However, in case of UK, France and Germany negative relation between CO 2 emission and GDP per capita is observed.In case of fast growing economies viz.India, China, Indonesia, Malaysia and Bangladesh direct positive relation is found.In case of USA, Canada and Japan, a different 'N' shaped curve is observed.In this study it is found that CO 2 emission depends upon complex interactions of all three variables i.e. population pressure, economic growth and technology.The countries like Germany, France and UK where the policies of environmental protection are widely adopted and clean technologies are used in energy production CO 2 emission has been contained.The least developed economies like Liberia, Rwanda and Madagascar are causing severe damage to the environment.In present scenario of globalization the most harmful factor for release of CO 2 is economic growth in developed and developing economies.However, in case of least developed economies technological factor is responsible for greater damage.It is also found that CO 2 emission does not follow inverted 'U' shaped curve as has been envisaged in Environmental -Kuznets -Curve.i Dedicated ToThe cause of Mother Earth
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".