Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014
Understanding the spatial heterogeneity and driving force identification of energy-related CO2 emissions (ECEs) can help build consensus for mitigating CO2 emissions and designing appropriate policies. However, previous studies on ECEs that focus on both the global-regional scale and the interaction...
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MDPI AG
2017-03-01
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Series: | Energies |
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Online Access: | http://www.mdpi.com/1996-1073/10/3/367 |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yebing Fang Limao Wang Zhoupeng Ren Yan Yang Chufu Mou Qiushi Qu |
spellingShingle |
Yebing Fang Limao Wang Zhoupeng Ren Yan Yang Chufu Mou Qiushi Qu Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014 Energies energy-related carbon emissions determinant factors spatial heterogeneity geographical detector growth rate |
author_facet |
Yebing Fang Limao Wang Zhoupeng Ren Yan Yang Chufu Mou Qiushi Qu |
author_sort |
Yebing Fang |
title |
Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014 |
title_short |
Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014 |
title_full |
Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014 |
title_fullStr |
Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014 |
title_full_unstemmed |
Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014 |
title_sort |
spatial heterogeneity of energy-related co2 emission growth rates around the world and their determinants during 1990–2014 |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2017-03-01 |
description |
Understanding the spatial heterogeneity and driving force identification of energy-related CO2 emissions (ECEs) can help build consensus for mitigating CO2 emissions and designing appropriate policies. However, previous studies on ECEs that focus on both the global-regional scale and the interaction of factors have been seldom conducted. In this paper, ECE data from 143 countries from 1990 to 2014 were selected to analyze regional differences in ECE growth rates by using the coefficient of variation. Then a geographical detector was used to analyze the key determinant factors on ECE growth rates around the world and in eight types of regions. The results show that: (1) the ECE growth rate in the Organization for Economic Cooperation and Development (OECD) region is low and tended to decrease, while in the non-OECD region it is high and tended to increase; (2) the coefficient of variation and detection factor of ECE growth rates at a regional scale are higher than those at a global scale; (3) in terms of the key determinant factors, population growth rate, growth rate of per capita GDP, and energy intensity growth rate are the three key determinant factors of ECE growth rates in the OECD region and most of the non-OECD regions such as non-OECD European and Eurasian (NO-EE), Asia (NO-AS), non-OECD Americas (NO-AM). The key determinant factors in the African (NO-AF) region are population growth rates and natural gas carbon intensity growth rates. The key determinant factors of the Middle East (NO-ME) are population growth rate, coal carbon intensity growth rate and per capita GDP growth rate; (4) the determinant power of the detection factor, the population growth rate at the global scale and regional scale is the strongest, showing a significant spatial consistency. The determinant power of per capita GDP growth rate and energy intensity growth rate in the OECD region, respectively, rank second and third, also showing a spatial consistency. However, the carbon intensity growth rates of the three fossil fuels contribute little to the growth rate of ECEs, and their spatial coherence is weak; (5) from the perspective of the interaction of detection factors, six detection factors showed bilinear or non-linear enhancement at a global and a regional scale, and the determinant power of the interaction of factors was significantly enhanced; and (6) from the perspective of ecological detection, the growth rate of carbon intensity and the growth rate of natural gas carbon intensity at the global scale and NO-ME region are significantly stronger than other factors, with a significant difference in the spatial distribution of its incidence. Therefore, the OECD region should continue to reduce the growth of energy intensity, and develop alternative energy resources in the future, while those that are plagued by carbon emissions in non-OECD regions should pay more attention to the positive influence of lower population growth rates on reducing the growth rate of energy-related CO2 emissions. Reducing energy intensity growth rates and reducing, fossil energy consumption carbon intensity. |
topic |
energy-related carbon emissions determinant factors spatial heterogeneity geographical detector growth rate |
url |
http://www.mdpi.com/1996-1073/10/3/367 |
work_keys_str_mv |
AT yebingfang spatialheterogeneityofenergyrelatedco2emissiongrowthratesaroundtheworldandtheirdeterminantsduring19902014 AT limaowang spatialheterogeneityofenergyrelatedco2emissiongrowthratesaroundtheworldandtheirdeterminantsduring19902014 AT zhoupengren spatialheterogeneityofenergyrelatedco2emissiongrowthratesaroundtheworldandtheirdeterminantsduring19902014 AT yanyang spatialheterogeneityofenergyrelatedco2emissiongrowthratesaroundtheworldandtheirdeterminantsduring19902014 AT chufumou spatialheterogeneityofenergyrelatedco2emissiongrowthratesaroundtheworldandtheirdeterminantsduring19902014 AT qiushiqu spatialheterogeneityofenergyrelatedco2emissiongrowthratesaroundtheworldandtheirdeterminantsduring19902014 |
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doaj-25a4c38ba366494fb3953cc55d4480e12020-11-24T23:58:08ZengMDPI AGEnergies1996-10732017-03-0110336710.3390/en10030367en10030367Spatial Heterogeneity of Energy-Related CO2 Emission Growth Rates around the World and Their Determinants during 1990–2014Yebing Fang0Limao Wang1Zhoupeng Ren2Yan Yang3Chufu Mou4Qiushi Qu5Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaThe CAE Center for Strategic Studies, Chinese Academy of Engineering, Beijing 100088, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaInstitute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaUnderstanding the spatial heterogeneity and driving force identification of energy-related CO2 emissions (ECEs) can help build consensus for mitigating CO2 emissions and designing appropriate policies. However, previous studies on ECEs that focus on both the global-regional scale and the interaction of factors have been seldom conducted. In this paper, ECE data from 143 countries from 1990 to 2014 were selected to analyze regional differences in ECE growth rates by using the coefficient of variation. Then a geographical detector was used to analyze the key determinant factors on ECE growth rates around the world and in eight types of regions. The results show that: (1) the ECE growth rate in the Organization for Economic Cooperation and Development (OECD) region is low and tended to decrease, while in the non-OECD region it is high and tended to increase; (2) the coefficient of variation and detection factor of ECE growth rates at a regional scale are higher than those at a global scale; (3) in terms of the key determinant factors, population growth rate, growth rate of per capita GDP, and energy intensity growth rate are the three key determinant factors of ECE growth rates in the OECD region and most of the non-OECD regions such as non-OECD European and Eurasian (NO-EE), Asia (NO-AS), non-OECD Americas (NO-AM). The key determinant factors in the African (NO-AF) region are population growth rates and natural gas carbon intensity growth rates. The key determinant factors of the Middle East (NO-ME) are population growth rate, coal carbon intensity growth rate and per capita GDP growth rate; (4) the determinant power of the detection factor, the population growth rate at the global scale and regional scale is the strongest, showing a significant spatial consistency. The determinant power of per capita GDP growth rate and energy intensity growth rate in the OECD region, respectively, rank second and third, also showing a spatial consistency. However, the carbon intensity growth rates of the three fossil fuels contribute little to the growth rate of ECEs, and their spatial coherence is weak; (5) from the perspective of the interaction of detection factors, six detection factors showed bilinear or non-linear enhancement at a global and a regional scale, and the determinant power of the interaction of factors was significantly enhanced; and (6) from the perspective of ecological detection, the growth rate of carbon intensity and the growth rate of natural gas carbon intensity at the global scale and NO-ME region are significantly stronger than other factors, with a significant difference in the spatial distribution of its incidence. Therefore, the OECD region should continue to reduce the growth of energy intensity, and develop alternative energy resources in the future, while those that are plagued by carbon emissions in non-OECD regions should pay more attention to the positive influence of lower population growth rates on reducing the growth rate of energy-related CO2 emissions. Reducing energy intensity growth rates and reducing, fossil energy consumption carbon intensity.http://www.mdpi.com/1996-1073/10/3/367energy-related carbon emissionsdeterminant factorsspatial heterogeneitygeographical detectorgrowth rate |