Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes...
Ausführliche Beschreibung
Autor*in: |
Lihong Peng [verfasserIn] Yi Zhang [verfasserIn] Feng Li [verfasserIn] Qian Wang [verfasserIn] Xiaochou Chen [verfasserIn] Ang Yu [verfasserIn] |
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E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2019 |
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Übergeordnetes Werk: |
In: Nuclear Engineering and Technology - Elsevier, 2016, 51(2019), 4, Seite 1154-1162 |
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Übergeordnetes Werk: |
volume:51 ; year:2019 ; number:4 ; pages:1154-1162 |
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DOI / URN: |
10.1016/j.net.2019.01.016 |
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Katalog-ID: |
DOAJ051727560 |
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10.1016/j.net.2019.01.016 doi (DE-627)DOAJ051727560 (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10 DE-627 ger DE-627 rakwb eng TK9001-9401 Lihong Peng verfasserin aut Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model Nuclear engineering. Atomic power Yi Zhang verfasserin aut Feng Li verfasserin aut Qian Wang verfasserin aut Xiaochou Chen verfasserin aut Ang Yu verfasserin aut In Nuclear Engineering and Technology Elsevier, 2016 51(2019), 4, Seite 1154-1162 (DE-627)63243855X (DE-600)2566624-1 17385733 nnns volume:51 year:2019 number:4 pages:1154-1162 https://doi.org/10.1016/j.net.2019.01.016 kostenfrei https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 kostenfrei http://www.sciencedirect.com/science/article/pii/S1738573318307551 kostenfrei https://doaj.org/toc/1738-5733 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2019 4 1154-1162 |
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10.1016/j.net.2019.01.016 doi (DE-627)DOAJ051727560 (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10 DE-627 ger DE-627 rakwb eng TK9001-9401 Lihong Peng verfasserin aut Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model Nuclear engineering. Atomic power Yi Zhang verfasserin aut Feng Li verfasserin aut Qian Wang verfasserin aut Xiaochou Chen verfasserin aut Ang Yu verfasserin aut In Nuclear Engineering and Technology Elsevier, 2016 51(2019), 4, Seite 1154-1162 (DE-627)63243855X (DE-600)2566624-1 17385733 nnns volume:51 year:2019 number:4 pages:1154-1162 https://doi.org/10.1016/j.net.2019.01.016 kostenfrei https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 kostenfrei http://www.sciencedirect.com/science/article/pii/S1738573318307551 kostenfrei https://doaj.org/toc/1738-5733 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2019 4 1154-1162 |
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10.1016/j.net.2019.01.016 doi (DE-627)DOAJ051727560 (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10 DE-627 ger DE-627 rakwb eng TK9001-9401 Lihong Peng verfasserin aut Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model Nuclear engineering. Atomic power Yi Zhang verfasserin aut Feng Li verfasserin aut Qian Wang verfasserin aut Xiaochou Chen verfasserin aut Ang Yu verfasserin aut In Nuclear Engineering and Technology Elsevier, 2016 51(2019), 4, Seite 1154-1162 (DE-627)63243855X (DE-600)2566624-1 17385733 nnns volume:51 year:2019 number:4 pages:1154-1162 https://doi.org/10.1016/j.net.2019.01.016 kostenfrei https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 kostenfrei http://www.sciencedirect.com/science/article/pii/S1738573318307551 kostenfrei https://doaj.org/toc/1738-5733 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2019 4 1154-1162 |
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10.1016/j.net.2019.01.016 doi (DE-627)DOAJ051727560 (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10 DE-627 ger DE-627 rakwb eng TK9001-9401 Lihong Peng verfasserin aut Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model Nuclear engineering. Atomic power Yi Zhang verfasserin aut Feng Li verfasserin aut Qian Wang verfasserin aut Xiaochou Chen verfasserin aut Ang Yu verfasserin aut In Nuclear Engineering and Technology Elsevier, 2016 51(2019), 4, Seite 1154-1162 (DE-627)63243855X (DE-600)2566624-1 17385733 nnns volume:51 year:2019 number:4 pages:1154-1162 https://doi.org/10.1016/j.net.2019.01.016 kostenfrei https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 kostenfrei http://www.sciencedirect.com/science/article/pii/S1738573318307551 kostenfrei https://doaj.org/toc/1738-5733 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2019 4 1154-1162 |
allfieldsSound |
10.1016/j.net.2019.01.016 doi (DE-627)DOAJ051727560 (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10 DE-627 ger DE-627 rakwb eng TK9001-9401 Lihong Peng verfasserin aut Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model Nuclear engineering. Atomic power Yi Zhang verfasserin aut Feng Li verfasserin aut Qian Wang verfasserin aut Xiaochou Chen verfasserin aut Ang Yu verfasserin aut In Nuclear Engineering and Technology Elsevier, 2016 51(2019), 4, Seite 1154-1162 (DE-627)63243855X (DE-600)2566624-1 17385733 nnns volume:51 year:2019 number:4 pages:1154-1162 https://doi.org/10.1016/j.net.2019.01.016 kostenfrei https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 kostenfrei http://www.sciencedirect.com/science/article/pii/S1738573318307551 kostenfrei https://doaj.org/toc/1738-5733 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 51 2019 4 1154-1162 |
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After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. 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Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China |
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China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model |
abstractGer |
China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model |
abstract_unstemmed |
China is undertaking an energy reform from fossil fuels to clean energy to accomplish CO2 intensity (CI) reduction commitments. After hydropower, nuclear energy is potential based on breadthwise comparison with the world and analysis of government energy consumption (EC) plan. This paper establishes a CI energy policy response forecasting model based on national and provincial EC plans. This model is then applied in Fujian Province to predict its CI from 2016 to 2020. The result shows that CI declines at a range of 43%–53% compared to that in 2005 considering five conditions of economic growth in 2020. Furthermore, Fujian will achieve the national goals in advance because EC is controlled and nuclear energy ratio increased to 16.4% (the proportion of non-fossil in primary energy is 26.7%). Finally, the development of nuclear energy in China and the world are analyzed, and several policies for energy optimization and CI reduction are proposed. Keywords: CO2 intensity reduction, Energy structure optimization, Nuclear energy, CO2 intensity energy policy response forecasting model |
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score |
7.4014273 |