• 4차산업연구
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• 제3권2호
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• pp.1-10
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• 2023

Purpose - The main purpose of the paper is to examine the variables affecting carbon emissions in different nations around the world. Research design, data, and methodology - To measure its impact on carbon emissions, secondary data has data of the top 50 Countries have been taken. The stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model have been used to quantify the factors that affect carbon emissions. A modified version using Industry 4.0 and region in fundamental STIRPAT model has been applied with the ordinary least square approach. The outcome has been measured using both the basic and extended STIRPAT models. Result - Technology found a positive determinant as well as statistically significant at the alpha level of 0.001models indicating that technological innovation helps reduce carbon emissions. In total, 4 models have been derived to test the best fit and find the highest explaining capacity of variance. Model 3 is found best fit in explanatory power with the highest adjusted R2 (97.95%). Conclusion - It can be concluded that the selected explanatory variables population and Industry 4.0 are found important indicators and causal factors for carbon emission and found constant with all four models for total CO2 and Co2 per capita.

• Environmental Engineering Research
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• 제21권1호
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• pp.74-83
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• 2016

The purpose of this study is to identify the driven factors affecting the changes in energy-related $CO_2$ emissions in Hebei Province of China from 1995 to 2013. This study confirmed that energy-related $CO_2$ emissions are correlated with the population, urbanization level, economic development degree, industry structure, foreign trade degree, technology level and energy proportion through an improved STIRPAT model. A reasonable and more reliable outcome of STIRPAT model can be obtained with the introducing of the Ridge Regression, which shows that population is the most important factor for $CO_2$ emissions in Hebei with the coefficient 2.4528. Rely on these discussions about affect abilities of each driven factors, we conclude several proposals to arrive targets for reductions in Hebei's energy-related $CO_2$ emissions. The method improved and relative policy advance improved pointing at empirical results also can be applied by other province to make study about driven factors of the growth of carbon emissions.

• 한국경제지리학회지
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• 제24권4호
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• pp.400-410
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• 2021

본 연구는 2000년부터 2019년까지 우리나라 16개 광역시·도의 패널자료를 활용하여 확장된 STIRPAT 모형을 통해 이산화탄소 배출량 결정요인을 분석하였다. 패널 데이터의 횡단면 의존성과 계수 이질성을 검정한 후, 이들 특성을 반영한 MG, CCEMG, AMG 추정법을 통해 분석하였다. AMG 추정법을 통해 분석한 결과를 살펴보면, 소득, 인구, 에너지 집약도의 계수가 양(+)의 부호로 통계적으로 유의하게 나타났으나, 도시화는 통계적으로 유의하지 않는 것으로 나타났다. 우리나라 이산화탄소 배출량의 감소는 에너지 효율의 증가와 지속가능한 경제성장을 통해 이루어질 수 있다. 따라서 이산화탄소 감축기술의 적극적인 개발로 저탄소 사회를 구축하고, 이와 함께 기술혁신을 통해 장기적으로 생산성 향상을 유발하여 지속가능한 경제성장에 기여할 수 있는 정책수립이 필요하다.

• 동아시아경상학회지
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• 제2권4호
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• pp.1-8
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• 2014

This study examines the relationship between population growth and carbon dioxide emissions in the context of Africa perspective. Population growth and carbon dioxide emissions helped identify the key driving forces of environmental impacts by including other predictors in all the different income levels of all sampled countries in Africa. To explore the role of population growth in the emissions of carbon dioxide, this research employed a panel data set of 52 Africa countries from 1960 to 2012 using fixed effects, random effects and GLS/FGLS estimators to estimate the modified STIRPAT model. The results found that a 1% increase in population growth suggests an increase in carbon dioxide emission loads by about 0.33%, 1.08%, 0.57% and 2.32% on the average, controlling for all other anthropogenic driving forces, for LICA, LMICA, UICA and HICA respectively. There is a significant relationship between population growth and carbon dioxide emissions in all the national income levels in Africa.