text:
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Number-of-Cited-References = {{44}},
Times-Cited = {{5}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Aust. J. Soc. Iss.}},
Doc-Delivery-Number = {{GV0CG}},
Unique-ID = {{ISI:000445723600005}},
OA = {{Green Accepted, Other Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000442433200005,
Author = {Liu, Bo and Huang, Gang and Hu, Kaiming and Wu, Renguang and Gong,
   Hainan and Wang, Pengfei and Zhao, Guijie},
Title = {{The multidecadal variations of the interannual relationship between the
   East Asian summer monsoon and ENSO in a coupled model}},
Journal = {{CLIMATE DYNAMICS}},
Year = {{2018}},
Volume = {{51}},
Number = {{5-6}},
Pages = {{1671-1686}},
Month = {{SEP}},
Abstract = {{This study investigates the multidecadal variations of the interannual
   relationship between the East Asian summer monsoon (EASM) and El
   Nio-Southern Oscillation (ENSO) in 1000-year simulation of a coupled
   climate model. The interannual relationship between ENSO and EASM has
   experienced pronounced changes throughout the 1000-year simulation.
   During the periods with significant ENSO-EASM relationship, the
   ENSO-related circulation anomalies show a Pacific-Japan (PJ)-like
   pattern with significant wave-activity flux propagating from the tropics
   to the north in lower troposphere and from the mid-latitudes to the
   south in upper troposphere. The resultant ENSO-related precipitation
   anomalies are more (less) than normal over the East Asia (western North
   Pacific) in the decaying summers of El Nio events. In contrast, the
   circulation and precipitation anomalies are weak over East Asia-western
   North Pacific during the periods with weak ENSO-EASM relationship. Based
   on the energy conversion analysis, the related anomalies achieve
   barotropic and baroclinic energy from the mean flow during the periods
   with strong ENSO-EASM relationship. On the contrary, during the
   low-correlation periods, the energy conversion is too weak to form the
   link between the tropics and mid-latitudes. The main reason for the
   multidecadal variations of ENSO-EASM relationship is the amplitude
   discrepancy of SST anomalies over the Indo-western Pacific Ocean which,
   in turn, leads to the intensity difference of the western North Pacific
   anomalous anticyclone (WPAC) and related climate anomalies.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Huang, G (Corresponding Author), Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci \& Geop, Beijing 100029, Peoples R China.
   Huang, G (Corresponding Author), Joint Ctr Global Change Studies, Beijing 100875, Peoples R China.
   Huang, G (Corresponding Author), Univ Chinese Acad Sci, Coll Earth Sci, Beijing 100049, Peoples R China.
   Huang, G (Corresponding Author), Qingdao Natl Lab Marine Sci \& Technol, Lab Reg Oceanog \& Numer Modeling, Qingdao 266237, Peoples R China.
   Liu, Bo; Huang, Gang; Hu, Kaiming; Wang, Pengfei; Zhao, Guijie, Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci \& Geop, Beijing 100029, Peoples R China.
   Hu, Kaiming; Wu, Renguang; Gong, Hainan; Wang, Pengfei; Zhao, Guijie, Chinese Acad Sci, Inst Atmospher Phys, Ctr Monsoon Syst Res, Beijing 100190, Peoples R China.
   Huang, Gang, Joint Ctr Global Change Studies, Beijing 100875, Peoples R China.
   Liu, Bo; Huang, Gang, Univ Chinese Acad Sci, Coll Earth Sci, Beijing 100049, Peoples R China.
   Huang, Gang, Qingdao Natl Lab Marine Sci \& Technol, Lab Reg Oceanog \& Numer Modeling, Qingdao 266237, Peoples R China.
   Zhao, Guijie, Beijing Meteorol Observ, Beijing 100089, Peoples R China.}},
DOI = {{10.1007/s00382-017-3976-3}},
ISSN = {{0930-7575}},
EISSN = {{1432-0894}},
Keywords = {{East Asian Summer monsoon; ENSO; Coupled climate model; Interannual;
   Multidecadal variations}},
Keywords-Plus = {{INDO-WESTERN PACIFIC; EL-NINO; NORTHWEST PACIFIC; OCEAN INTERACTION;
   CLIMATE; TELECONNECTION; VARIABILITY; IMPACT; PROPAGATION; DEPENDENCE}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{hg@mail.iap.ac.cn}},
ResearcherID-Numbers = {{Gong, Hainan/R-2934-2019
   Wang, Pengfei/K-5757-2013
   huang, gang/D-6427-2012}},
ORCID-Numbers = {{Gong, Hainan/0000-0002-6501-162X
   huang, gang/0000-0002-8692-7856}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}41425019, 41721004, 41661144016, 41376112];
   Public Science and Technology Research Funds Projects of Ocean
   {[}201505013]; CAS Key Technology Talent Program}},
Funding-Text = {{This work was supported by the National Natural Science Foundation of
   China (41425019, 41721004, 41661144016 and 41376112) and the Public
   Science and Technology Research Funds Projects of Ocean (201505013) and
   the CAS Key Technology Talent Program.}},
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Number-of-Cited-References = {{48}},
Times-Cited = {{6}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{Clim. Dyn.}},
Doc-Delivery-Number = {{GR2SQ}},
Unique-ID = {{ISI:000442433200005}},
DA = {{2020-08-06}},
}

@article{ ISI:000442433200023,
Author = {Ding, Shuoyi and Chen, Wen and Graf, Hans-F. and Guo, Yuanyuan and Nath,
   Debashis},
Title = {{Distinct winter patterns of tropical Pacific convection anomaly and the
   associated extratropical wave trains in the Northern Hemisphere}},
Journal = {{CLIMATE DYNAMICS}},
Year = {{2018}},
Volume = {{51}},
Number = {{5-6}},
Pages = {{2003-2022}},
Month = {{SEP}},
Abstract = {{In this paper, distinct patterns of boreal winter convection anomalies
   over the tropical Pacific and associated wave trains in the extratropics
   are addressed. The first leading mode (EOF1) of convection anomalies as
   measured by outgoing longwave radiation demonstrates an east-west
   oscillation of deep convection with centers over the equatorial central
   Pacific (CP) and over the tropical western North Pacific and the
   Maritime Continent. The second leading mode (EOF2) is also a dipole
   pattern with opposite centers straddling 170A degrees W, possibly
   modifying EOF1 to some extent. Combining the first two leading modes,
   five major categories of tropical convection anomalies can be identified
   for the period 1979/80-2012/13. The comparison between these five
   categories and the corresponding SST anomaly patterns indicates a
   nonlinear relationship between convection and SST. The combination of
   EOF1 and EOF2 with in-phase PCs exhibits an east-west dipole pattern
   with opposite signs over west of the dateline and the Maritime
   Continent. The negative phase of the two PCs, named La Nia pattern,
   induces a negative Pacific/North American-positive North Atlantic
   Oscillation teleconnection in the extratropics. Approximately opposite
   responses can be detected in its positive phase, named CP El Nio
   pattern. The negative PC2 superposing positive PC1, named EP El Nio
   pattern, shows the strongest convection anomalies with enhanced
   (depressed) convection over the eastern (western) Pacific and leads to a
   Tropical/Northern Hemisphere-like teleconnection pattern and an
   anomalous anticyclone extending from the North Pacific to the North
   Atlantic. The positive PC2 with neutral PC1, named western CP pattern,
   shows weakly enhanced convection to the west of the dateline as a
   response to local SST warming around the dateline. This convection
   anomaly pattern, although weak, is important and excites a northeastward
   wave train from the tropics to Greenland, resulting in surface air
   temperature cooling covering the northeastern North America and warmer
   and wetter conditions over Western Europe.}},
Publisher = {{SPRINGER}},
Address = {{ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Chen, W (Corresponding Author), Chinese Acad Sci, Inst Atmospher Phys, Ctr Monsoon Syst Res, Beijing 100190, Peoples R China.
   Chen, W (Corresponding Author), Univ Chinese Acad Sci, Sch Earth Sci, Beijing, Peoples R China.
   Ding, Shuoyi; Chen, Wen; Graf, Hans-F.; Nath, Debashis, Chinese Acad Sci, Inst Atmospher Phys, Ctr Monsoon Syst Res, Beijing 100190, Peoples R China.
   Ding, Shuoyi; Chen, Wen, Univ Chinese Acad Sci, Sch Earth Sci, Beijing, Peoples R China.
   Guo, Yuanyuan, Sun Yat Sen Univ, Sch Atmospher Sci, Ctr Monsoon \& Environm Res, Guangzhou, Guangdong, Peoples R China.}},
DOI = {{10.1007/s00382-017-3995-0}},
ISSN = {{0930-7575}},
EISSN = {{1432-0894}},
Keywords = {{Tropical Pacific convection; Extratropical wave train; Western CP
   pattern; Indonesia West Pacific dipole; CP and EP El Nino}},
Keywords-Plus = {{OUTGOING LONGWAVE RADIATION; NINO-SOUTHERN OSCILLATION; TERM CLIMATE
   VARIABILITY; EL-NINO; ATMOSPHERIC CIRCULATION; INTERANNUAL SEESAW;
   AMERICAN CLIMATE; WESTERN PACIFIC; ICELANDIC LOWS; ENSO INFLUENCE}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{chenw@mail.iap.ac.cn}},
ResearcherID-Numbers = {{Chen, Wen/G-6058-2011}},
ORCID-Numbers = {{Chen, Wen/0000-0001-9327-9079}},
Funding-Acknowledgement = {{National Key Research and Development Program {[}2016YFA0600604];
   Chinese Academy of Sciences Key Research Program of Frontier Sciences
   {[}QYZDY-SSW-DQC024]; ``The Belt and Road Initiatives{''} Program on
   International Cooperation: Climate Change Research and Observation
   Project {[}134111KYSB20160010]}},
Funding-Text = {{We thank the two anonymous reviewers for their very constructive
   comments and suggestions, which led to significant improvement in the
   manuscript. This study is supported jointly by the National Key Research
   and Development Program (Grant no. 2016YFA0600604), the Chinese Academy
   of Sciences Key Research Program of Frontier Sciences (QYZDY-SSW-DQC024)
   and ``The Belt and Road Initiatives{''} Program on International
   Cooperation: Climate Change Research and Observation Project
   (134111KYSB20160010).}},
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Number-of-Cited-References = {{59}},
Times-Cited = {{5}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{9}},
Journal-ISO = {{Clim. Dyn.}},
Doc-Delivery-Number = {{GR2SQ}},
Unique-ID = {{ISI:000442433200023}},
DA = {{2020-08-06}},
}

@article{ ISI:000442433200041,
Author = {Datwyler, Christoph and Neukom, Raphael and Abram, Nerilie J. and
   Gallant, Ailie J. E. and Grosjean, Martin and Jacques-Coper, Martin and
   Karoly, David J. and Villalba, Ricardo},
Title = {{Teleconnection stationarity, variability and trends of the Southern
   Annular Mode (SAM) during the last millennium}},
Journal = {{CLIMATE DYNAMICS}},
Year = {{2018}},
Volume = {{51}},
Number = {{5-6}},
Pages = {{2321-2339}},
Month = {{SEP}},
Abstract = {{The Southern Annular Mode (SAM) is the leading mode of atmospheric
   interannual variability in the Southern Hemisphere (SH) extra-tropics.
   Here, we assess the stationarity of SAM spatial correlations with
   instrumental and paleoclimate proxy data for the past millennium. The
   instrumental period shows that temporal non-stationarities in SAM
   teleconnections are not consistent across the SH land areas. This
   suggests that the influence of the SAM index is modulated by regional
   effects. However, within key-regions with good proxy data coverage
   (South America, Tasmania, New Zealand), teleconnections are mostly
   stationary over the instrumental period. Using different stationarity
   criteria for proxy record selection, we provide new austral summer and
   annual mean SAM index reconstructions over the last millennium. Our
   summer SAM reconstructions are very robust to changes in proxy record
   selection and the selection of the calibration period, particularly on
   the multi-decadal timescale. In contrast, the weaker performance and
   lower agreement in the annual mean SAM reconstructions point towards
   changing teleconnection patterns that may be particularly important
   outside the summer months. Our results clearly portend that the temporal
   stationarity of the proxy-climate relationships should be taken into
   account in the design of comprehensive regional and hemispherical
   climate reconstructions. The summer SAM reconstructions show no
   significant relationship to solar, greenhouse gas and volcanic forcing,
   with the exception of an extremely strong negative anomaly following the
   AD 1257 Samalas eruption. Furthermore, reconstructed pre-industrial
   summer SAM trends are very similar to trends obtained by model control
   simulations. We find that recent trends in the summer SAM lie outside
   the 5-95\% range of pre-industrial natural variability.}},
Publisher = {{SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Datwyler, C (Corresponding Author), Univ Bern, Inst Geog, CH-3012 Bern, Switzerland.
   Datwyler, C (Corresponding Author), Univ Bern, Oeschger Ctr Climate Change Res, CH-3012 Bern, Switzerland.
   Datwyler, Christoph; Neukom, Raphael; Grosjean, Martin, Univ Bern, Inst Geog, CH-3012 Bern, Switzerland.
   Datwyler, Christoph; Neukom, Raphael; Grosjean, Martin, Univ Bern, Oeschger Ctr Climate Change Res, CH-3012 Bern, Switzerland.
   Abram, Nerilie J., Australian Natl Univ, Res Sch Earth Sci, Canberra, ACT, Australia.
   Abram, Nerilie J., Australian Natl Univ, ARC Ctr Excellence Climate Syst Sci, Canberra, ACT, Australia.
   Gallant, Ailie J. E., Monash Univ, Sch Earth Atmosphere \& Environm, Clayton, Vic 3800, Australia.
   Jacques-Coper, Martin, Univ Concepcion, Dept Geofis, Concepcion, Chile.
   Jacques-Coper, Martin, Univ Concepcion, Ctr Climate \& Resilience Res, Concepcion, Chile.
   Karoly, David J., Univ Melbourne, Sch Earth Sci, Melbourne, Vic 3010, Australia.
   Karoly, David J., Univ Melbourne, ARC Ctr Excellence Climate Syst Sci, Melbourne, Vic 3010, Australia.
   Villalba, Ricardo, CCT CONICET, Inst Argentino Nivol Glaciol \& Ciencias Ambiental, RA-5500 Mendoza, Argentina.}},
DOI = {{10.1007/s00382-017-4015-0}},
ISSN = {{0930-7575}},
EISSN = {{1432-0894}},
Keywords = {{Climate change; Climate reconstruction; Paleoclimate; Southern
   Hemisphere; Holocene}},
Keywords-Plus = {{SEA-LEVEL PRESSURE; VOLCANIC-ERUPTIONS; TEMPERATURE RECONSTRUCTIONS;
   HEMISPHERE CIRCULATION; ANTARCTIC OSCILLATION; SURFACE-TEMPERATURE;
   CLIMATE-CHANGE; PART I; DECADAL VARIATIONS; PAST MILLENNIUM}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{christoph.daetwyler@giub.unibe.ch}},
ResearcherID-Numbers = {{Karoly, David J/C-8262-2011
   }},
ORCID-Numbers = {{Karoly, David J/0000-0002-8671-2994
   Gallant, Ailie/0000-0002-7917-1069
   Neukom, Raphael/0000-0001-9392-0997
   Datwyler, Christoph/0000-0002-9923-4311
   Villalba, Ricardo/0000-0001-8183-0310
   Abram, Nerilie/0000-0003-1246-2344}},
Funding-Acknowledgement = {{Swiss National Science Foundation (SNF) Ambizione grantSwiss National
   Science Foundation (SNSF) {[}PZ00P2\_154802]; Australian Research
   Council Centre of Excellence for Climate System ScienceAustralian
   Research Council {[}CE110001028]; CONICYT-ChileComision Nacional de
   Investigacion Cientifica y Tecnologica (CONICYT) {[}PAI79160105,
   FONDAP15110009]}},
Funding-Text = {{This is a contribution to the Past Global Changes (PAGES) 2k Network.
   Researchers from the PAGES2k consortium are acknowledged for providing
   access to data and metadata information. We thank Michael N. Evans for
   discussions. This study was supported by the Swiss National Science
   Foundation (SNF) Ambizione grant PZ00P2\_154802. DJK receives funding
   through the Australian Research Council Centre of Excellence for Climate
   System Science (CE110001028). MJC acknowledges CONICYT-Chile through
   grants PAI79160105 and FONDAP15110009. RN, MG, and CD designed the
   study; CD and RN led the writing and conducted the data analysis. All
   authors jointly discussed and contributed to the writing.}},
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Times-Cited = {{16}},
Usage-Count-Last-180-days = {{4}},
Usage-Count-Since-2013 = {{20}},
Journal-ISO = {{Clim. Dyn.}},
Doc-Delivery-Number = {{GR2SQ}},
Unique-ID = {{ISI:000442433200041}},
DA = {{2020-08-06}},
}

@article{ ISI:000452692100027,
Author = {Li, Chunhui and Xu, Meng and Wang, Xuan and Tan, Qian},
Title = {{Spatial analysis of dual-scale water stresses based on water footprint
   accounting in the Haihe River Basin, China}},
Journal = {{ECOLOGICAL INDICATORS}},
Year = {{2018}},
Volume = {{92}},
Pages = {{254-267}},
Month = {{SEP}},
Abstract = {{Water scarcity and degradation of water quality in river basins are
   among the major issues addressed by water resources management
   authorities. Moreover, two typical challenges associated with water
   resources management include naturally unbalanced distribution and
   administrative disparities under multiple jurisdictions at the watershed
   scale. Effective accounting and management methods are thus desired to
   deal with such challenges. Water footprint accounting is widely used for
   assessing natural water resources availability and supporting optimal
   allocation among multiple jurisdictions, representing a useful tool for
   improving watershed sustainability. Not only will this enable successful
   revealing of the direct water consumption by relevant agents, but also
   indirect water consumption by concerning users. Such a method is
   particularly useful for addressing water-related issues in numerous
   watersheds of developing countries, which are subject to diverse water
   stressors. Hence, this study aimed at conducting water footprint
   accounting under city/regional and basin scales for the investigation of
   the amounts of blue and gray water in the Haihe River Basin (HRB),
   China. The Blue Water Footprint Index (BWFI) and the Gray Water
   Footprint Capacity Coefficient (K) were introduced to comprehensively
   evaluate water scarcity in terms of quantity and quality. The results
   revealed that all cities of the HRB suffered from extreme water
   scarcity. The industrial sector was identified as the primary
   contributor to the blue water footprint at the watershed. The
   agricultural gray-water footprint of the HRB accounted for 54\% of the
   total. The exploratory spatial data analysis (ESDA) was adopted to
   analyze the spatial auto-correlation features of blue and gray water in
   the HRB. The results indicated that Dezhou and Binzhou had the highest
   water deficiency in both of the water stresses, and that Xinxiang,
   Puyang, Anyang and Jiaozuo had the highest water problem predominantly
   due to water quality stress.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tan, Q (Corresponding Author), China Agr Univ, Coll Water Resources \& Civil Engn, Beijing 100083, Peoples R China.
   Li, Chunhui; Xu, Meng; Wang, Xuan, Beijing Normal Univ, Sch Environm, Key Lab Water \& Sand Sci, Minist Educ, Beijing 100875, Peoples R China.
   Xu, Meng, Zhejiang Univ Finance \& Econ, Sch Publ Adm, Hangzhou 310018, Zhejiang, Peoples R China.
   Tan, Qian, China Agr Univ, Coll Water Resources \& Civil Engn, Beijing 100083, Peoples R China.
   Li, Chunhui; Wang, Xuan, Beijing Normal Univ, Sch Environm, State Key Lab Water Environm Simulat, Beijing 100875, Peoples R China.}},
DOI = {{10.1016/j.ecolind.2017.02.046}},
ISSN = {{1470-160X}},
EISSN = {{1872-7034}},
Keywords = {{Blue water footprint; Gray water footprint; Haihe River Basin;
   Exploratory spatial data analysis; Water footprint accounting}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; VIRTUAL WATER; DECOMPOSITION ANALYSIS; TRADE;
   TRANSFERS; FLOWS; GLOBALIZATION; CONSUMPTION; RESOURCES; PRODUCTS}},
Research-Areas = {{Biodiversity \& Conservation; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Biodiversity Conservation; Environmental Sciences}},
Author-Email = {{qian\_tan@cau.edu.cn}},
Funding-Acknowledgement = {{National Key Research and Development Program {[}2016YFC0401302];
   Zhejiang Social Science Program {[}12JCJJ10YB]; Social Science Project
   of Education Department of Zhejiang Province}},
Funding-Text = {{This research was supported by the National Key Research and Development
   Program (2016YFC0401302), the Zhejiang Social Science Program
   (12JCJJ10YB), and the Social Science Project of Education Department of
   Zhejiang Province (Sustainable Development of Coastal Areas based on
   Ecosystem Analysis). In addition, we also acknowledge the editor and
   anonymous reviewers for their valuable suggestions and comments on our
   manuscript.}},
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Number-of-Cited-References = {{56}},
Times-Cited = {{9}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{33}},
Journal-ISO = {{Ecol. Indic.}},
Doc-Delivery-Number = {{HD6WX}},
Unique-ID = {{ISI:000452692100027}},
DA = {{2020-08-06}},
}

@article{ ISI:000449891600026,
Author = {Wen, Fenghua and Ye, Zhengke and Yang, Huaidong and Li, Ke},
Title = {{Exploring the rebound effect from the perspective of household: An
   analysis of China's provincial level}},
Journal = {{ENERGY ECONOMICS}},
Year = {{2018}},
Volume = {{75}},
Pages = {{345-356}},
Month = {{SEP}},
Abstract = {{The existence of the energy rebound effect may partially even totally
   offset the expected energy savings. In order to explore the status of
   the household rebound effect in China, we manually compiled the
   provincial energy input-output table of China. Then, combining
   econometric methods, input-output analysis and the re-spending model, we
   conduct a detailed analysis of both the direct and indirect energy
   rebound effect from the household perspective in China under a unified
   research framework. The results show there are significant differences
   in risk vulnerability regarding energy rebound effect among different
   regions. Qinghai is the most vulnerable province as 69.23\% of its
   economic sectors could lead to a backfire effect. Two economic sectors
   have the potential to cause a backfire effect in thirteen provinces. In
   addition, the Chinese government and its provincial government should
   take full account of the regional differences when formulating energy
   policies to alleviate the pressure on energy conservation and carbon
   emission reduction. (C) 2018 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Li, K (Corresponding Author), Hunan Normal Univ, Key Lab High Performance Comp \& Stochast Informat, Coll Math \& Stat, Minist Educ China, Changsha 410081, Hunan, Peoples R China.
   Wen, Fenghua; Ye, Zhengke; Yang, Huaidong, Cent S Univ, Business Sch, Changsha 410083, Hunan, Peoples R China.
   Wen, Fenghua, Univ Windsor, Fac Engn, Supply Chain \& Logist Optimizat Res Ctr, Windsor, ON, Canada.
   Li, Ke, Hunan Normal Univ, Key Lab High Performance Comp \& Stochast Informat, Coll Math \& Stat, Minist Educ China, Changsha 410081, Hunan, Peoples R China.}},
DOI = {{10.1016/j.eneco.2018.08.018}},
ISSN = {{0140-9883}},
EISSN = {{1873-6181}},
Keywords = {{Rebound effect; Household energy consumption; Input-output analysis;
   Risk vulnerability; China}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; RESIDENTIAL ELECTRICITY CONSUMPTION; GENERAL
   EQUILIBRIUM-ANALYSIS; ENERGY EFFICIENCY; PASSENGER TRANSPORT; ECONOMY;
   CONSERVATION; HETEROGENEITY; SUBSIDIES; INDUSTRY}},
Research-Areas = {{Business \& Economics}},
Web-of-Science-Categories  = {{Economics}},
Author-Email = {{like@hunnu.edu.cn}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71873146, 71773028, 71873147, 71431008];
   Education Department of Hunan Province {[}17A142]; International Clean
   Energy Talent Programme {[}LIUJINFA{[}2017]5047-201702660011]}},
Funding-Text = {{Our deepest gratitude goes to the anonymous reviewers for their careful
   work and constructive suggestions that have helped improve this paper
   substantially. We gratefully acknowledge the financial support from the
   National Natural Science Foundation of China (nos. 71873146, 71773028,
   71873147, 71431008), the Education Department of Hunan Province (no.
   17A142) and the International Clean Energy Talent Programme (no.
   LIUJINFA{[}2017]5047-201702660011).}},
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Usage-Count-Last-180-days = {{4}},
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Journal-ISO = {{Energy Econ.}},
Doc-Delivery-Number = {{HA0IL}},
Unique-ID = {{ISI:000449891600026}},
DA = {{2020-08-06}},
}

@article{ ISI:000440123300014,
Author = {Kis, Zoltan and Pandya, Nikul and Koppelaar, Rembrandt H. E. M.},
Title = {{Electricity generation technologies: Comparison of materials use, energy
   return on investment, jobs creation and CO2 emissions reduction}},
Journal = {{ENERGY POLICY}},
Year = {{2018}},
Volume = {{120}},
Pages = {{144-157}},
Month = {{SEP}},
Abstract = {{Shifting to a low-carbon electricity future requires up-to-date
   information on the energetic, environmental and socio-economic
   performance of technologies. Here, we present a novel comprehensive
   bottom-up process chain framework that is applied to 19 electricity
   generation technologies, consistently incorporating 12 life-cycle phases
   from extraction to decommissioning. For each life-cycle phase of each
   technology the following 4 key metrics were assessed: material
   consumption, energy return ratios, job requirements and greenhouse gas
   emissions. We also calculate a novel global electricity to grid average
   for these metrics and present a metric variability analysis by altering
   transport distance, load factors, efficiency, and fuel density per
   technology. This work quantitatively supports model-to-policy frameworks
   that drive technology selection and investment based on
   energetic-economic viability, job creation and carbon emission reduction
   of technologies. The results suggest energetic-economic infeasibility of
   electricity generation networks with substantial shares of: i) liquefied
   natural gas transport, ii) long distance transport based hard and brown
   coal and pipeline natural gas, and iii) low-load factor
   solar-photovoltaic, concentrated solar power, onshore and offshore wind.
   Direct sector jobs can be expected to double in renewable-majority
   scenarios. All combustion-powered technologies without natural
   (bio-mass) or artificial carbon capture (fossil fuels) are not
   compatible with a low carbon electricity generation future.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Koppelaar, RHEM (Corresponding Author), Scene Connect Ltd, 465c Hornsey Rd, London N19 4DR, England.
   Kis, Zoltan; Pandya, Nikul, Imperial Coll London, Dept Chem Engn, Fac Engn, South Kensington Campus, London SW7 2AZ, England.
   Koppelaar, Rembrandt H. E. M., Scene Connect Ltd, 465c Hornsey Rd, London N19 4DR, England.}},
DOI = {{10.1016/j.enpol.2018.05.033}},
ISSN = {{0301-4215}},
EISSN = {{1873-6777}},
Keywords = {{Electricity technology comparison; Net electricity; Electricity
   generation supply chain; Electricity generation jobs; Electricity
   generation greenhouse gas emissions}},
Keywords-Plus = {{LIFE-CYCLE ASSESSMENT; PHOTOVOLTAIC SOLAR-SYSTEMS;
   INPUT-OUTPUT-ANALYSIS; NATURAL-GAS; MODERATE INSOLATION; RENEWABLE
   ENERGY; ASSESSMENT LCA; BRIDGE FUEL; EROI; REGIONS}},
Research-Areas = {{Business \& Economics; Energy \& Fuels; Environmental Sciences \&
   Ecology}},
Web-of-Science-Categories  = {{Economics; Energy \& Fuels; Environmental Sciences; Environmental
   Studies}},
Author-Email = {{rembrandtkoppelaar@protonmail.com}},
ResearcherID-Numbers = {{Kis, Zoltan/H-3611-2016}},
ORCID-Numbers = {{Kis, Zoltan/0000-0002-6598-8369}},
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Number-of-Cited-References = {{67}},
Times-Cited = {{8}},
Usage-Count-Last-180-days = {{6}},
Usage-Count-Since-2013 = {{62}},
Journal-ISO = {{Energy Policy}},
Doc-Delivery-Number = {{GO6DC}},
Unique-ID = {{ISI:000440123300014}},
DA = {{2020-08-06}},
}

@article{ ISI:000444459300008,
Author = {Sun, Lu and Li, Zhaoling and Fujii, Minoru and Hijioka, Yasuaki and
   Fujita, Tsuyoshi},
Title = {{Carbon footprint assessment for the waste management sector: A
   comparative analysis of China and Japan}},
Journal = {{FRONTIERS IN ENERGY}},
Year = {{2018}},
Volume = {{12}},
Number = {{3, SI}},
Pages = {{400-410}},
Month = {{SEP}},
Abstract = {{Waste management is becoming a crucial issue in modern society owing to
   rapid urbanization and the increasing generation of municipal solid
   waste (MSW). This paper evaluates the carbon footprint of the waste
   management sector to identify direct and indirect carbon emissions,
   waste recycling carbon emission using a hybrid life cycle assessment and
   input-output analysis. China and Japan was selected as case study areas
   to highlight the effects of different industries on waste management.
   The results show that the life cycle carbon footprints for waste
   treatment are 59.01 million tons in China and 7.01 million tons in
   Japan. The gap between these footprints is caused by the different waste
   management systems and treatment processes used in the two countries.
   For indirect carbon footprints, China's material carbon footprint and
   depreciation carbon footprint are much higher than those of Japan,
   whereas the purchased electricity and heat carbon footprint in China is
   half that of Japan. China and Japan have similar direct energy
   consumption carbon footprints. However, CO2 emissions from MSW treatment
   processes in China (46.46 million tons) is significantly higher than
   that in Japan (2.72 million tons). The corresponding effects of waste
   recycling on CO2 emission reductions are considerable, up to 181.37
   million tons for China and 96.76 million tons for Japan. Besides,
   measures were further proposed for optimizing waste management systems
   in the two countries. In addition, it is argued that the advanced
   experience that developed countries have in waste management issues can
   provide scientific support for waste treatment in developing countries
   such as China.}},
Publisher = {{HIGHER EDUCATION PRESS}},
Address = {{NO 4 DEWAI DAJIE, BEIJING 100120, PEOPLES R CHINA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Li, ZL (Corresponding Author), Natl Inst Environm Studies, Ctr Social \& Environm Syst Res, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan.
   Sun, Lu, Univ Tokyo, Grad Sch Frontier Sci, Dept Environm Syst, 5-1-5 Kashiwanoha, Kashiwa, Chiba 2778563, Japan.
   Sun, Lu; Li, Zhaoling; Fujii, Minoru; Hijioka, Yasuaki; Fujita, Tsuyoshi, Natl Inst Environm Studies, Ctr Social \& Environm Syst Res, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan.
   Li, Zhaoling, Univ Tsukuba, Grad Sch Life \& Environm Sci, Tsukuba, Ibaraki 3058506, Japan.}},
DOI = {{10.1007/s11708-018-0565-z}},
ISSN = {{2095-1701}},
EISSN = {{2095-1698}},
Keywords = {{waste management; waste recycling; carbon footprint; hybrid LCA}},
Keywords-Plus = {{LIFE-CYCLE ASSESSMENT; CO2 EMISSIONS; INDUSTRIAL SYMBIOSIS;
   DEVELOPING-COUNTRIES; URBAN SYMBIOSIS; STEEL-INDUSTRY; TO-ENERGY;
   REDUCTION; CITY; INCINERATION}},
Research-Areas = {{Energy \& Fuels}},
Web-of-Science-Categories  = {{Energy \& Fuels}},
Author-Email = {{li.zhaoling@nies.go.jp}},
ResearcherID-Numbers = {{Hijioka, Yasuaki/AAQ-7586-2020
   Sun, Lu/L-2238-2019}},
ORCID-Numbers = {{Sun, Lu/0000-0001-7356-7866}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71461137008, 71325006, 71311140172]; Environment
   Research and Technology Development Fund {[}3K1709, 3K163001]; Key
   Technology of IOT Big Data Platform for the Periodic Renting Electric
   Vehicles {[}16511105204]}},
Funding-Text = {{This work was supported by the National Natural Science Foundation of
   China (Grant Nos. 71461137008, 71325006, and 71311140172), the
   Environment Research and Technology Development Fund (3K1709 and
   3K163001) and Key Technology of IOT Big Data Platform for the Periodic
   Renting Electric Vehicles (No. 16511105204).}},
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Number-of-Cited-References = {{34}},
Times-Cited = {{3}},
Usage-Count-Last-180-days = {{13}},
Usage-Count-Since-2013 = {{50}},
Journal-ISO = {{Front. Energy}},
Doc-Delivery-Number = {{GT4FJ}},
Unique-ID = {{ISI:000444459300008}},
DA = {{2020-08-06}},
}

@article{ ISI:000443683600011,
Author = {Carrillo, Carlos M. and Castro, Christopher L. and Garfin, Gregg and
   Chang, Hsin-I and Bukovsky, Melissa S. and Mearns, Linda O.},
Title = {{Pacific sea surface temperature related influences on North American
   monsoon precipitation within North American Regional Climate Change
   Assessment Program models}},
Journal = {{INTERNATIONAL JOURNAL OF CLIMATOLOGY}},
Year = {{2018}},
Volume = {{38}},
Number = {{11}},
Pages = {{4189-4210}},
Month = {{SEP}},
Abstract = {{Climate inter-annual variability over the North American monsoon (NAM)
   region is associated with El Nino-Southern Oscillation (ENSO) and
   Pacific decadal variability (PDV), which drive a warm season atmospheric
   teleconnection response. Using the North American Regional Climate
   Change Assessment Program (NARCCAP) simulations, previous studies have
   found that regional models forced with an atmospheric reanalysis
   (NARCCAP Phase I) represent the NAM reasonably well as a climatological
   feature. However, when these same regional models are forced with global
   climate model projections (NARCCAP Phase II), their ability to represent
   the NAM as a salient feature substantially degrades. The present study
   evaluates NAM inter-annual climate variability through the
   continental-scale patterns of summer precipitation within the NARCCAP
   simulations (Phases I and II), in relation to ENSO-PDV, and the presence
   of the driving atmospheric teleconnection response. Multivariate
   statistical analyses are applied to sea surface temperature and
   precipitation data sets to determine dominant variability at continental
   scale, with focus on the southwest. The analysis reveals that NARCCAP
   Phase I simulations are able to portray the spatial pattern of
   precipitation associated with ENSO-PDV in a similar way to observations.
   However, all NARCCAP Phase II simulations, with the exception of the
   HRM(Hadcm3) regional-global model pair, fail to reproduce this climate
   variability. Although including all possible NARCCAP model simulations
   to generate a multi-model ensemble mean would increase the statistical
   degree of confidence in climate projections, this type of result would
   not increase confidence in the physical climatology of model
   representations of warm season climate variability. More physically
   based, process-oriented metrics are needed to evaluate model quality in
   assessing the uncertainty of future climate change in multi-model
   ensemble products used for climate change impacts assessments.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Carrillo, CM (Corresponding Author), Univ Arizona, Dept Atmospher Sci, Phys \& Atmospher Sci Bldg,Rm 536, Tucson, AZ 85721 USA.
   Carrillo, Carlos M.; Castro, Christopher L.; Chang, Hsin-I, Univ Arizona, Dept Atmospher Sci, Phys \& Atmospher Sci Bldg,Rm 536, Tucson, AZ 85721 USA.
   Carrillo, Carlos M., Cornell Univ, Dept Earth \& Atmospher Sci, Ithaca, NY USA.
   Garfin, Gregg, Univ Arizona, Inst Environm, Sch Nat Resources \& Environm, Tucson, AZ USA.
   Bukovsky, Melissa S.; Mearns, Linda O., Natl Ctr Atmospher Res, POB 3000, Boulder, CO 80307 USA.}},
DOI = {{10.1002/joc.5561}},
ISSN = {{0899-8418}},
EISSN = {{1097-0088}},
Keywords = {{ENSO-PDV; MTM-SVD; NAM; NARCCAP}},
Keywords-Plus = {{OBSERVATIONAL RECORD; UNITED-STATES; TIME-SERIES; SYSTEM RAMS; PART II;
   VARIABILITY; CMIP5; SIMULATIONS; PROJECTIONS; FORECAST}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{carloscc@email.arizona.edu}},
Funding-Acknowledgement = {{City of Tucson Office of Conservation and Sustainable Development;
   National Science Foundation (NSF)National Science Foundation (NSF);
   Climate Assessment for the Southwest (CLIMAS) at the University of
   Arizona; Water Sustainability Graduate Student Fellowship Program}},
Funding-Text = {{City of Tucson Office of Conservation and Sustainable Development;
   National Science Foundation (NSF); Climate Assessment for the Southwest
   (CLIMAS) at the University of Arizona; The Water Sustainability Graduate
   Student Fellowship Program}},
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