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

Gespeichert in:

Autor*in:	Lihong Peng [verfasserIn] Yi Zhang [verfasserIn] Feng Li [verfasserIn] Qian Wang [verfasserIn] Xiaochou Chen [verfasserIn] Ang Yu [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Übergeordnetes Werk:	In: Nuclear Engineering and Technology - Elsevier, 2016, 51(2019), 4, Seite 1154-1162
Übergeordnetes Werk:	volume:51 ; year:2019 ; number:4 ; pages:1154-1162

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.net.2019.01.016

Katalog-ID:	DOAJ051727560

Internformat


LEADER	01000caa a22002652 4500
001	DOAJ051727560
003	DE-627
005	20230308162539.0
007	cr uuu---uuuuu
008	230227s2019 xx \|\|\|\|\|o 00\| \|\|eng c
024	7		\|a 10.1016/j.net.2019.01.016 \|2 doi
035			\|a (DE-627)DOAJ051727560
035			\|a (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10
040			\|a DE-627 \|b ger \|c DE-627 \|e rakwb
041			\|a eng
050		0	\|a TK9001-9401
100	0		\|a Lihong Peng \|e verfasserin \|4 aut
245	1	0	\|a Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
264		1	\|c 2019
336			\|a Text \|b txt \|2 rdacontent
337			\|a Computermedien \|b c \|2 rdamedia
338			\|a Online-Ressource \|b cr \|2 rdacarrier
520			\|a 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
653		0	\|a Nuclear engineering. Atomic power
700	0		\|a Yi Zhang \|e verfasserin \|4 aut
700	0		\|a Feng Li \|e verfasserin \|4 aut
700	0		\|a Qian Wang \|e verfasserin \|4 aut
700	0		\|a Xiaochou Chen \|e verfasserin \|4 aut
700	0		\|a Ang Yu \|e verfasserin \|4 aut
773	0	8	\|i In \|t Nuclear Engineering and Technology \|d Elsevier, 2016 \|g 51(2019), 4, Seite 1154-1162 \|w (DE-627)63243855X \|w (DE-600)2566624-1 \|x 17385733 \|7 nnns
773	1	8	\|g volume:51 \|g year:2019 \|g number:4 \|g pages:1154-1162
856	4	0	\|u https://doi.org/10.1016/j.net.2019.01.016 \|z kostenfrei
856	4	0	\|u https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 \|z kostenfrei
856	4	0	\|u http://www.sciencedirect.com/science/article/pii/S1738573318307551 \|z kostenfrei
856	4	2	\|u https://doaj.org/toc/1738-5733 \|y Journal toc \|z kostenfrei
912			\|a GBV_USEFLAG_A
912			\|a SYSFLAG_A
912			\|a GBV_DOAJ
912			\|a GBV_ILN_20
912			\|a GBV_ILN_22
912			\|a GBV_ILN_23
912			\|a GBV_ILN_24
912			\|a GBV_ILN_31
912			\|a GBV_ILN_39
912			\|a GBV_ILN_40
912			\|a GBV_ILN_60
912			\|a GBV_ILN_62
912			\|a GBV_ILN_63
912			\|a GBV_ILN_65
912			\|a GBV_ILN_69
912			\|a GBV_ILN_70
912			\|a GBV_ILN_73
912			\|a GBV_ILN_95
912			\|a GBV_ILN_105
912			\|a GBV_ILN_110
912			\|a GBV_ILN_151
912			\|a GBV_ILN_161
912			\|a GBV_ILN_170
912			\|a GBV_ILN_213
912			\|a GBV_ILN_230
912			\|a GBV_ILN_285
912			\|a GBV_ILN_293
912			\|a GBV_ILN_370
912			\|a GBV_ILN_602
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4037
912			\|a GBV_ILN_4112
912			\|a GBV_ILN_4125
912			\|a GBV_ILN_4126
912			\|a GBV_ILN_4249
912			\|a GBV_ILN_4305
912			\|a GBV_ILN_4306
912			\|a GBV_ILN_4307
912			\|a GBV_ILN_4313
912			\|a GBV_ILN_4322
912			\|a GBV_ILN_4323
912			\|a GBV_ILN_4324
912			\|a GBV_ILN_4325
912			\|a GBV_ILN_4335
912			\|a GBV_ILN_4338
912			\|a GBV_ILN_4367
912			\|a GBV_ILN_4700
951			\|a AR
952			\|d 51 \|j 2019 \|e 4 \|h 1154-1162

Indexfelder

author_variant	l p lp y z yz f l fl q w qw x c xc a y ay
matchkey_str	article:17385733:2019----::oiymlctooncernryptniloeegotmztoadomtg
hierarchy_sort_str	2019
callnumber-subject-code	TK
publishDate	2019
allfields	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
spelling	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
allfields_unstemmed	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
allfieldsGer	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
language	English
source	In Nuclear Engineering and Technology 51(2019), 4, Seite 1154-1162 volume:51 year:2019 number:4 pages:1154-1162
sourceStr	In Nuclear Engineering and Technology 51(2019), 4, Seite 1154-1162 volume:51 year:2019 number:4 pages:1154-1162
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Nuclear engineering. Atomic power
isfreeaccess_bool	true
container_title	Nuclear Engineering and Technology
authorswithroles_txt_mv	Lihong Peng @@aut@@ Yi Zhang @@aut@@ Feng Li @@aut@@ Qian Wang @@aut@@ Xiaochou Chen @@aut@@ Ang Yu @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
hierarchy_top_id	63243855X
id	DOAJ051727560
language_de	englisch
fullrecord	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ051727560</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230308162539.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.net.2019.01.016</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ051727560</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TK9001-9401</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Lihong Peng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Nuclear engineering. Atomic power</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yi Zhang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Feng Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qian Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xiaochou Chen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ang Yu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Nuclear Engineering and Technology</subfield><subfield code="d">Elsevier, 2016</subfield><subfield code="g">51(2019), 4, Seite 1154-1162</subfield><subfield code="w">(DE-627)63243855X</subfield><subfield code="w">(DE-600)2566624-1</subfield><subfield code="x">17385733</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:51</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:4</subfield><subfield code="g">pages:1154-1162</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.net.2019.01.016</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/article/pii/S1738573318307551</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1738-5733</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">51</subfield><subfield code="j">2019</subfield><subfield code="e">4</subfield><subfield code="h">1154-1162</subfield></datafield></record></collection>
callnumber-first	T - Technology
author	Lihong Peng
spellingShingle	Lihong Peng misc TK9001-9401 misc Nuclear engineering. Atomic power Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
authorStr	Lihong Peng
ppnlink_with_tag_str_mv	@@773@@(DE-627)63243855X
format	electronic Article
delete_txt_mv	keep
author_role	aut aut aut aut aut aut
collection	DOAJ
remote_str	true
callnumber-label	TK9001-9401
illustrated	Not Illustrated
issn	17385733
topic_title	TK9001-9401 Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
topic	misc TK9001-9401 misc Nuclear engineering. Atomic power
topic_unstemmed	misc TK9001-9401 misc Nuclear engineering. Atomic power
topic_browse	misc TK9001-9401 misc Nuclear engineering. Atomic power
format_facet	Elektronische Aufsätze Aufsätze Elektronische Ressource
format_main_str_mv	Text Zeitschrift/Artikel
carriertype_str_mv	cr
hierarchy_parent_title	Nuclear Engineering and Technology
hierarchy_parent_id	63243855X
hierarchy_top_title	Nuclear Engineering and Technology
isfreeaccess_txt	true
familylinks_str_mv	(DE-627)63243855X (DE-600)2566624-1
title	Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
ctrlnum	(DE-627)DOAJ051727560 (DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10
title_full	Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
author_sort	Lihong Peng
journal	Nuclear Engineering and Technology
journalStr	Nuclear Engineering and Technology
callnumber-first-code	T
lang_code	eng
isOA_bool	true
recordtype	marc
publishDateSort	2019
contenttype_str_mv	txt
container_start_page	1154
author_browse	Lihong Peng Yi Zhang Feng Li Qian Wang Xiaochou Chen Ang Yu
container_volume	51
class	TK9001-9401
format_se	Elektronische Aufsätze
author-letter	Lihong Peng
doi_str_mv	10.1016/j.net.2019.01.016
author2-role	verfasserin
title_sort	policy implication of nuclear energy’s potential for energy optimization and co2 mitigation: a case study of fujian, china
callnumber	TK9001-9401
title_auth	Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
abstract	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
collection_details	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
container_issue	4
title_short	Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China
url	https://doi.org/10.1016/j.net.2019.01.016 https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10 http://www.sciencedirect.com/science/article/pii/S1738573318307551 https://doaj.org/toc/1738-5733
remote_bool	true
author2	Yi Zhang Feng Li Qian Wang Xiaochou Chen Ang Yu
author2Str	Yi Zhang Feng Li Qian Wang Xiaochou Chen Ang Yu
ppnlink	63243855X
callnumber-subject	TK - Electrical and Nuclear Engineering
mediatype_str_mv	c
isOA_txt	true
hochschulschrift_bool	false
doi_str	10.1016/j.net.2019.01.016
callnumber-a	TK9001-9401
up_date	2024-07-03T21:57:58.262Z
_version_	1803596729735446529
fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ051727560</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230308162539.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230227s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.net.2019.01.016</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ051727560</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJ29ef0a4e2c3d4a4eb665c62647e6af10</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TK9001-9401</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Lihong Peng</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Nuclear engineering. Atomic power</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Yi Zhang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Feng Li</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Qian Wang</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Xiaochou Chen</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="0" ind2=" "><subfield code="a">Ang Yu</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">In</subfield><subfield code="t">Nuclear Engineering and Technology</subfield><subfield code="d">Elsevier, 2016</subfield><subfield code="g">51(2019), 4, Seite 1154-1162</subfield><subfield code="w">(DE-627)63243855X</subfield><subfield code="w">(DE-600)2566624-1</subfield><subfield code="x">17385733</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:51</subfield><subfield code="g">year:2019</subfield><subfield code="g">number:4</subfield><subfield code="g">pages:1154-1162</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.net.2019.01.016</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doaj.org/article/29ef0a4e2c3d4a4eb665c62647e6af10</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">http://www.sciencedirect.com/science/article/pii/S1738573318307551</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">https://doaj.org/toc/1738-5733</subfield><subfield code="y">Journal toc</subfield><subfield code="z">kostenfrei</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_DOAJ</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_23</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_31</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_39</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_62</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_63</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_65</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_69</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_73</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_95</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_110</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_151</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_161</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_213</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_230</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_293</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_602</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2014</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4037</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4112</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4125</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4126</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4249</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4306</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4322</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4323</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4325</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4335</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4338</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4367</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4700</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">51</subfield><subfield code="j">2019</subfield><subfield code="e">4</subfield><subfield code="h">1154-1162</subfield></datafield></record></collection>
score	7.4014273

Nicht das Richtige dabei?

Schreiben Sie uns!

Policy implication of nuclear energy’s potential for energy optimization and CO2 mitigation: A case study of Fujian, China

Nicht das Richtige dabei?

Zugang & Verfügbarkeit

Vorhandene Bände

Nicht das Richtige dabei?