text:
sector.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Zhao, X (Corresponding Author), Hohai Univ, Coll Environm, Minist Educ, Key Lab Integrated Regulat \& Resource Dev Shallow, Nanjing 210098, Jiangsu, Peoples R China.
   Liao, Xiawei; Hall, Jim W., Univ Oxford, Environm Change Inst, Oxford OX1 3QY, England.
   Zhao, Xu, Hohai Univ, Coll Environm, Minist Educ, Key Lab Integrated Regulat \& Resource Dev Shallow, Nanjing 210098, Jiangsu, Peoples R China.
   Guan, Dabo, Univ East Anglia, Sch Int Dev, Water Secur Res Ctr, Norwich NR4 7TJ, Norfolk, England.}},
DOI = {{10.1016/j.apenergy.2018.05.132}},
ISSN = {{0306-2619}},
EISSN = {{1872-9118}},
Keywords = {{Electric power; Water-energy nexus; Virtual water; Multi-regional
   input-output analysis}},
Keywords-Plus = {{THERMOELECTRIC-POWER; GENERATION; STRESS; SYSTEM; SCALE}},
Research-Areas = {{Energy \& Fuels; Engineering}},
Web-of-Science-Categories  = {{Energy \& Fuels; Engineering, Chemical}},
Author-Email = {{xuzhao@hhu.edu.cn}},
ResearcherID-Numbers = {{Zhao, Xu/A-6972-2015
   Guan, Dabo/Y-2406-2019
   Liao, Xiawei/AAG-3183-2019}},
ORCID-Numbers = {{Zhao, Xu/0000-0002-7461-852X
   Guan, Dabo/0000-0003-3773-3403
   }},
Funding-Acknowledgement = {{China Scholarship Council Oxford University Scholarship; Fundamental
   Research Funds for the Central UniversitiesFundamental Research Funds
   for the Central Universities {[}2016B13814, 2016B06814]; National
   Natural Science Foundation of ChinaNational Natural Science Foundation
   of China {[}51779075]; CRSRI Open Research Program (2-D spatial-temporal
   investigation on water quality decoupling in the Yangtze River Estuary)
   {[}CKWV2017504/KY]}},
Funding-Text = {{This work was supported by the China Scholarship Council Oxford
   University Scholarship, the Fundamental Research Funds for the Central
   Universities (No. 2016B13814, 2016B06814), the National Natural Science
   Foundation of China (No.51779075), and CRSRI Open Research Program (2-D
   spatial-temporal investigation on water quality decoupling in the
   Yangtze River Estuary, CKWV2017504/KY). We thank Prof. Nick Eyre for his
   invaluable comments on this manuscript.}},
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Number-of-Cited-References = {{44}},
Times-Cited = {{22}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{32}},
Journal-ISO = {{Appl. Energy}},
Doc-Delivery-Number = {{GQ5AN}},
Unique-ID = {{ISI:000441688100020}},
OA = {{Green Accepted}},
DA = {{2020-08-06}},
}

@article{ ISI:000441688100086,
Author = {Li, Jia Shuo and Zhou, H. W. and Meng, Jing and Yang, Q. and Chen, B.
   and Zhang, Y. Y.},
Title = {{Carbon emissions and their drivers for a typical urban economy from
   multiple perspectives: A case analysis for Beijing city}},
Journal = {{APPLIED ENERGY}},
Year = {{2018}},
Volume = {{226}},
Pages = {{1076-1086}},
Month = {{SEP 15}},
Abstract = {{Understanding carbon emission profile of cities from multiple
   perspectives is a prerequisite to design just and effective carbon
   reduction policies. Previous studies on CO2 emissions by cities are
   usually confined to production or consumption-based perspective, while
   income-based perspective has been neglected. To fill the gap, direct
   emissions (a.k.a. production-based emissions), upstream emissions driven
   by final demand (a.k.a. consumption-based emissions) and downstream
   emissions enabled by primary input (a.k.a. income-based emissions) in an
   urban economy are comprehensively explored and compared for the first
   time, taking Beijing as a case. In the period of 2005-2012, Manufacture
   of Nonmetallic Mineral Products/Construction/Processing of Petroleum,
   Coking, Processing of Nuclear Fuel is identified as the key contributor
   to carbon emission by Beijing from the
   production/consumption/income-based perspective, respectively,
   indicating each perspective can unveil important information which the
   other methods fail to discover. Moreover, driving forces of CO2
   emissions change in Beijing are uncovered using the structural
   decomposition analysis (SDA) from both the demand and supply sides.
   Emission intensity, production input and output structure change
   contribute to CO2 emission decrease in Beijing, which are largely offset
   by population, final demand/primary input level and final demand/primary
   input structure change, resulting in a net 3.9 Mt reduction during
   2005-2012. While current policies continue to highlight end-of-pipe
   measures in cities, more attention should be paid to demand (e.g.,
   encouraging low-carbon consumption) and supply side (e.g., controlling
   capital investment in enterprises with large income-based CO2
   emissions).}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Peking Univ, Coll Engn, Lab Syst Ecol \& Sustainabil Sci, Beijing 100871, Peoples R China.
   Zhang, YY (Corresponding Author), Guangxi Univ, Guangxi Key Lab Power Syst Optimizat \& Energy Tec, Nanning 530004, Guangxi, Peoples R China.
   Li, Jia Shuo; Yang, Q., Huazhong Univ Sci \& Technol, State Key Lab Coal Combust, Wuhan 430074, Hubei, Peoples R China.
   Li, Jia Shuo; Yang, Q., Huazhong Univ Sci \& Technol, Sch Energy \& Power Engn, Dept New Energy Sci \& Engn, Wuhan 430074, Hubei, Peoples R China.
   Zhou, H. W., Tsinghua Univ, Tsinghua Berkeley Shenzhen Inst, Shenzhen Environm Sci \& New Energy Technol Engn L, Shenzhen 518055, Peoples R China.
   Meng, Jing, Univ Cambridge, Dept Polit \& Int Studies, Cambridge CB3 9DT, England.
   Chen, B., Peking Univ, Coll Engn, Lab Syst Ecol \& Sustainabil Sci, Beijing 100871, Peoples R China.
   Zhang, Y. Y., Guangxi Univ, Guangxi Key Lab Power Syst Optimizat \& Energy Tec, Nanning 530004, Guangxi, Peoples R China.}},
DOI = {{10.1016/j.apenergy.2018.06.004}},
ISSN = {{0306-2619}},
EISSN = {{1872-9118}},
Keywords = {{Urban CO2 emissions; Multiple accounting principles; Structural
   decomposition analysis; Beijing}},
Keywords-Plus = {{STRUCTURAL DECOMPOSITION ANALYSIS; GREENHOUSE-GAS EMISSIONS;
   INPUT-OUTPUT-ANALYSIS; GLOBAL CO2 EMISSIONS; ENERGY-WATER NEXUS;
   INTERNATIONAL-TRADE; GHG EMISSIONS; MERCURY EMISSIONS; DIOXIDE
   EMISSIONS; DRIVING FORCES}},
Research-Areas = {{Energy \& Fuels; Engineering}},
Web-of-Science-Categories  = {{Energy \& Fuels; Engineering, Chemical}},
Author-Email = {{chenbin0116@pku.edu.cn
   yiyizhang@gxu.edu.cn}},
ResearcherID-Numbers = {{YANG, QING/Y-8209-2018
   Chen, Bin/E-1760-2017
   Meng, Jing/J-9740-2013
   Li, Jiashuo/K-5809-2013
   Zhang, Yiyi/AAE-2510-2019
   }},
ORCID-Numbers = {{YANG, QING/0000-0003-4251-554X
   Chen, Bin/0000-0001-8326-4551
   Meng, Jing/0000-0001-8708-0485
   Li, Jiashuo/0000-0002-2915-4770
   Zhang, Yiyi/0000-0001-8785-126X}},
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Number-of-Cited-References = {{96}},
Times-Cited = {{56}},
Usage-Count-Last-180-days = {{12}},
Usage-Count-Since-2013 = {{104}},
Journal-ISO = {{Appl. Energy}},
Doc-Delivery-Number = {{GQ5AN}},
Unique-ID = {{ISI:000441688100086}},
ESI-Highly-Cited-Paper = {{Y}},
ESI-Hot-Paper = {{N}},
DA = {{2020-08-06}},
}

@article{ ISI:000439403000020,
Author = {Qian, Yiying and Dong, Huijuan and Geng, Yong and Zhong, Shaozhuo and
   Tian, Xu and Yu, Yanhong and Chen, Yihui and Moss, Dana Avery},
Title = {{Water footprint characteristic of less developed water-rich regions:
   Case of Yunnan, China}},
Journal = {{WATER RESEARCH}},
Year = {{2018}},
Volume = {{141}},
Pages = {{208-216}},
Month = {{SEP 15}},
Abstract = {{Rapid industrialization and urbanization pose pressure on water
   resources in China. Virtual water trade proves to be an increasingly
   useful tool in water stress alleviation for water-scarce regions, while
   bringing opportunities and challenges for less developed water-rich
   regions. In this study, Yunnan, a typical province in southwest China,
   was selected as the case study area to explore its potential in
   socioeconomic development in the context of water sustainability. Both
   input-output analysis and structural decomposition analysis on Yunnan's
   water footprint for the period of 2002-2012 were performed at not only
   an aggregated level but also a sectoral level. Results show that
   although the virtual water content of all economic sectors decreased due
   to technological progress, Yunnan's total water footprint still
   increased as a result of economic scale expansion. From the sectoral
   perspective, sectors with large water footprints include construction
   sector, agriculture sector, food manufacturing \& processing sector, and
   service sector, while metal products sector and food manufacturing \&
   processing sector were the major virtual water exporters, and textile \&
   clothing sector and construction sector were the major importers. Based
   on local conditions, policy suggestions were proposed, including
   economic structure and efficiency optimization, technology promotion and
   appropriate virtual water trade scheme. This study provides valuable
   insights for regions facing ``resource curse{''} by exploring potential
   socio-economic progress while ensuring water security. (C) 2018 Elsevier
   Ltd. All rights reserved.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Dong, HJ; Geng, Y (Corresponding Author), Shanghai Jiao Tong Univ, Sch Environm Sci \& Engn, Shanghai 200240, Peoples R China.
   Qian, Yiying; Dong, Huijuan; Geng, Yong; Zhong, Shaozhuo; Tian, Xu, Shanghai Jiao Tong Univ, Sch Environm Sci \& Engn, Shanghai 200240, Peoples R China.
   Geng, Yong, Shanghai Jiao Tong Univ, China Inst Urban Governance, Shanghai 200240, Peoples R China.
   Geng, Yong, Shanghai Inst Pollut Control \& Ecol Secur, Shanghai 200092, Peoples R China.
   Yu, Yanhong; Chen, Yihui, Yunnan Inst Environm Sci, Yunnan Key Lab Pollut Proc \& Management Plateau L, Kunming 650034, Yunnan, Peoples R China.
   Moss, Dana Avery, Univ Waterloo, Dept Geog, Fac Environm Studies, 200 Univ Ave West, Waterloo, ON N2L 3G1, Canada.}},
DOI = {{10.1016/j.watres.2018.03.075}},
ISSN = {{0043-1354}},
Keywords = {{Water footprint; Input-output analysis; Structural decomposition
   analysis; Water management; Yunnan; Governance}},
Keywords-Plus = {{STRUCTURAL DECOMPOSITION ANALYSIS; HAIHE RIVER-BASIN; VIRTUAL WATER; CO2
   EMISSIONS; TRADE; RESOURCES; FLOWS; TRANSFERS}},
Research-Areas = {{Engineering; Environmental Sciences \& Ecology; Water Resources}},
Web-of-Science-Categories  = {{Engineering, Environmental; Environmental Sciences; Water Resources}},
Author-Email = {{donghj@sjtu.edu.cn
   ygeng@sjtu.edu.cn}},
ResearcherID-Numbers = {{Geng, Yong/B-6310-2018
   }},
ORCID-Numbers = {{Geng, Yong/0000-0002-2284-1375
   Qian, Yiying/0000-0001-6737-2309
   Tian, Xu/0000-0003-3265-5725}},
Funding-Acknowledgement = {{Major Science and Technology Program for Water Pollution Control and
   Treatment {[}2017ZX07202]; Open Fund Program of Yunnan Key Laboratory;
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71603165, 71690241, 71325006, 71704104];
   Fundamental Research Funds for the Central Universities through Shanghai
   Jiao Tong University {[}16JCCS04]; Shanghai Municipal Government fund
   {[}17XD1401800]; Yunnan Research Academy of Environmental Science}},
Funding-Text = {{This study was sponsored by the Major Science and Technology Program for
   Water Pollution Control and Treatment (2017ZX07202), Open Fund Program
   of Yunnan Key Laboratory, the National Natural Science Foundation of
   China (71603165, 71690241, 71325006, 71704104), the Fundamental Research
   Funds for the Central Universities through Shanghai Jiao Tong University
   (16JCCS04), the Shanghai Municipal Government fund (17XD1401800), Yunnan
   Research Academy of Environmental Science.}},
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Number-of-Cited-References = {{46}},
Times-Cited = {{18}},
Usage-Count-Last-180-days = {{7}},
Usage-Count-Since-2013 = {{85}},
Journal-ISO = {{Water Res.}},
Doc-Delivery-Number = {{GN8IL}},
Unique-ID = {{ISI:000439403000020}},
DA = {{2020-08-06}},
}

@article{ ISI:000441688100090,
Author = {Heun, Matthew Kuperus and Owen, Anne and Brockway, Paul E.},
Title = {{A physical supply-use table framework for energy analysis on the energy
   conversion chain}},
Journal = {{APPLIED ENERGY}},
Year = {{2018}},
Volume = {{226}},
Pages = {{1134-1162}},
Month = {{SEP 15}},
Abstract = {{In response to the oil crises of the 1970s, energy accounting
   experienced a revolution and became the much broader field of energy
   analysis, in part by expanding along the energy conversion chain from
   primary and final energy to useful energy and energy services, which
   satisfy human needs. After evolution and specialization, the field of
   energy analysis today addresses topics along the entire energy
   conversion chain, including energy conversion systems, energy resources,
   carbon emissions, and the role of energy services in promoting human
   well-being and development. And the expanded field would benefit from a
   common analysis framework that provides data structure uniformity and
   methodological consistency.
   Building upon recent advances in related fields, we propose a physical
   supply-use table energy analysis framework consisting of four matrices
   from which the input-output structure of an energy conversion chain can
   be determined and the effects of changes in final demand can be
   estimated. Real-world examples demonstrate the physical supply-use table
   framework via investigation of energy analysis questions for a United
   Kingdom energy conversion chain.
   The physical supply use table framework has two key methodological
   advances over the building blocks that precede it, namely extending a
   common energy analysis framework through to energy services and
   application of physical supply-use tables to both energy and exergy
   analysis. The methodological advances enable the following first-time
   contributions to the literature: (1) performing energy and exergy
   analyses on an energy conversion chain using physical supply-use table
   matrices comprised of disaggregated products in physical units when the
   last stage is any of final energy, useful energy, or energy services;
   (2) performing structural path analysis on an energy conversion chain;
   and (3) developing and utilizing a matrix approach to inhomogeneous
   units. The framework spans the entire energy conversion chain and is
   suitable for many sub-fields of energy analysis, including net energy
   analysis, societal energy analysis, human needs and well-being, and
   structural path analysis, all of which are explored in this paper.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Heun, MK (Corresponding Author), Calvin Coll, Dept Engn, Grand Rapids, MI 49546 USA.
   Heun, Matthew Kuperus, Calvin Coll, Dept Engn, Grand Rapids, MI 49546 USA.
   Owen, Anne; Brockway, Paul E., Univ Leeds, Sustainabil Res Inst, Sch Earth \& Environm, Leeds LS2 9JT, W Yorkshire, England.}},
DOI = {{10.1016/j.apenergy.2018.05.109}},
ISSN = {{0306-2619}},
EISSN = {{1872-9118}},
Keywords = {{Physical supply-use table; Energy analysis; Energy conversion chain;
   Energy services; Structural path analysis; Input-output analysis}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; LIFE-CYCLE ASSESSMENT; ECONOMIC-GROWTH;
   DECOMPOSITION ANALYSIS; UNITED-STATES; SOCIOECONOMIC METABOLISM;
   PORTUGAL 1995-2010; MINIMUM EROI; BOTTOM-UP; EXERGY}},
Research-Areas = {{Energy \& Fuels; Engineering}},
Web-of-Science-Categories  = {{Energy \& Fuels; Engineering, Chemical}},
Author-Email = {{mIch2@calvin.edu}},
ORCID-Numbers = {{Owen, Anne/0000-0002-3872-9900
   Brockway, Paul/0000-0001-6925-8040
   Heun, Matthew/0000-0002-7438-214X}},
Funding-Acknowledgement = {{Calvin College sabbatical leave; UK Energy Research Centre (UKERC); UK
   Research Councils under EPSRC award {[}EP/L024756/1]; RCUK Energy
   Program {[}EP/N022645/1]}},
Funding-Text = {{Matthew Kuperus Heun was supported by a Calvin College sabbatical leave.
   Anne Owen's and Paul Brockway's time was funded as part of the research
   programme of the UK Energy Research Centre (UKERC), supported by the UK
   Research Councils under EPSRC award EP/L024756/1. Anne Owen's time was
   also supported by the RCUK Energy Program's funding for the Centre for
   Industrial Energy, Materials and Products {[}grant reference
   EP/N022645/1].}},
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Number-of-Cited-References = {{137}},
Times-Cited = {{10}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{8}},
Journal-ISO = {{Appl. Energy}},
Doc-Delivery-Number = {{GQ5AN}},
Unique-ID = {{ISI:000441688100090}},
OA = {{Other Gold, Green Published}},
DA = {{2020-08-06}},
}

@article{ ISI:000436599000055,
Author = {Martinez, Sara and del Mar Delgado, Maria and Martinez Marin, Ruben and
   Alvarez, Sergio},
Title = {{The environmental footprint of an organic peri-urban orchard network}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2018}},
Volume = {{636}},
Pages = {{569-579}},
Month = {{SEP 15}},
Abstract = {{Over the past years, the implementation of urban and peri-urban orchards
   in cities has increased and so has the environmental awareness regarding
   these systems. This study applied the environmental extended multi
   regional input-output analysis to obtain the Environmental Footprint
   associated with an organic peri-urban orchard network in Spain. The
   total environmental impacts were calculated for seven organic peri-urban
   orchards identified as PUO1 to PUO7. PUO1, PUO4 and PUO6 presented the
   highest environmental impacts due to a higher consumption of (1) fuel,
   (2) plastics and (3) electricity in comparison to the other orchards.
   Approximately 70\% of the overall impacts were indirect impacts
   generated in the supply chain. A more in-depth study of climate change
   impacts in the supply chain of the organic peri-urban orchard network
   revealed that the major hotspots were the sectors ``extraction of crude
   petroleum{''} (29\%) and ``production of electricity by gas and coal{''}
   (31\%) located in Spain, China and Middle East countries. The
   Environmental Footprint serves as a useful indicator to provide the
   environmental performance of an organic peri-urban orchard network and
   foster greener and more sustainable cities. (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 = {{Martinez, S (Corresponding Author), Univ Politecn Madrid, Dept Nat Syst \& Resources, Madrid, Spain.
   Martinez, Sara; Martinez Marin, Ruben; Alvarez, Sergio, Univ Politecn Madrid, Dept Land Morphol \& Engn, Madrid, Spain.
   Martinez, Sara, Univ Politecn Madrid, Dept Nat Syst \& Resources, Madrid, Spain.
   del Mar Delgado, Maria, INIA, Dept Environm, Ctra La Coruna Km 7,5, Madrid 28040, Spain.}},
DOI = {{10.1016/j.scitotenv.2018.04.340}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
Keywords = {{Peri-urban agriculture; Environmental impacts; Environmental extended
   multi-regional input-output analysis; Supply chain}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; URBAN AGRICULTURE; CARBON FOOTPRINTS; ENERGY;
   MRIO; PERFORMANCE; COMPANY; IMPACT; LCA}},
Research-Areas = {{Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Environmental Sciences}},
Author-Email = {{s.martinezd@alumnos.upm.es
   delgado@inia.es
   ruben.martinez@upm.es
   sergio.alvarez@upm.es}},
ResearcherID-Numbers = {{Alvarez, Sergio/H-9727-2015
   }},
ORCID-Numbers = {{Alvarez, Sergio/0000-0001-7204-502X
   Martinez Marin, Ruben/0000-0002-2433-9354}},
Funding-Acknowledgement = {{ {[}LIFE 12 ENV/ES/000919 Huertas Km0]}},
Funding-Text = {{Authors would like to thank the project LIFE 12 ENV/ES/000919 Huertas
   Km0, especially Dr. Rosa Duarte, Dr. Marisa Feijoo and Dr. Julia Merida
   Conde for providing the required information.}},
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Number-of-Cited-References = {{58}},
Times-Cited = {{5}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{22}},
Journal-ISO = {{Sci. Total Environ.}},
Doc-Delivery-Number = {{GK9TR}},
Unique-ID = {{ISI:000436599000055}},
DA = {{2020-08-06}},
}

@article{ ISI:000442849100008,
Author = {Chai, Rongfan and Sun, Shanlei and Chen, Haishan and Zhou, Shujia},
Title = {{Changes in reference evapotranspiration over China during 1960-2012:
   Attributions and relationships with atmospheric circulation}},
Journal = {{HYDROLOGICAL PROCESSES}},
Year = {{2018}},
Volume = {{32}},
Number = {{19}},
Pages = {{3032-3048}},
Month = {{SEP 15}},
Abstract = {{This study investigates reference evapotranspiration (ET0) trends in
   China from 1960 to 2012 based on the Penman-Monteith equation and
   gridded meteorological measurements. Under the combined impacts of
   factors influencing ET0(i.e., net radiation {[}RN], mean temperature
   {[}TAVE], vapour pressure deficit {[}VPD], and wind speed {[}WND]), both
   seasonal and annual ET0 for the whole China and more than half of the
   grids decreased over the past 53 years. The attribution analyses suggest
   that for the whole China, the WND is responsible for annual and seasonal
   ET0 decreases (excluding summer, where RN is responsible). Across China,
   the annual cause of WND with the largest spatial extent (43.1\% of
   grids) mainly derives from north of the Changjiang River Basin (CJRB),
   whereas VPD (RN) as a cause is dispersedly distributed (within and to
   the south of the CJRB). In summer, RN is dominant in more than half of
   the grids, but the dominance of VPD and WND accounts for approximately
   90\% of grids during the remaining seasons. Finally, the correlation
   coefficients between ET0 and the Atlantic Oscillation (AO), North AO,
   Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), and El
   Nino Southern Oscillation (ENSO) indices with different lead times are
   calculated. For the whole China, annual and seasonal ET0 always
   significantly correlate with these indices (excluding the IOD) but with
   varied lead times. Additionally, near half of the grids show significant
   and maximum (i.e., the largest one between ET0 and a certain index with
   a lead time of 0-3 seasons) correlation coefficients of ET0 with PDO in
   spring and summer, ENSO in autumn, and AO in winter. This study is not
   only significant for understanding ET0 changes, but it also provides
   preliminary and fundamental reference information for ET0 prediction.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sun, SL (Corresponding Author), Nanjing Univ Informat Sci \& Technol, Minist Educ, Key Lab Meteorol Disaster, Nanjing 210044, Jiangsu, Peoples R China.
   Chai, Rongfan; Sun, Shanlei; Chen, Haishan; Zhou, Shujia, NUIST, CIC FEMD, Int Joint Res Lab Climate \& Environm Change ILCEC, Key Lab Meteorol Disaster,Minist Educ KLME, Nanjing, Jiangsu, Peoples R China.
   Chai, Rongfan; Chen, Haishan; Zhou, Shujia, NUIST, Sch Atmospher Sci, Nanjing, Jiangsu, Peoples R China.}},
DOI = {{10.1002/hyp.13252}},
ISSN = {{0885-6087}},
EISSN = {{1099-1085}},
Keywords = {{attribution analysis; China; climate change; driving forces; reference
   evapotranspiration; teleconnection indices}},
Keywords-Plus = {{ASIAN SUMMER MONSOON; LAND-COVER CHANGE; INDIAN-OCEAN DIPOLE;
   CLIMATE-CHANGE; POTENTIAL EVAPOTRANSPIRATION; RIVER-BASIN;
   SPATIOTEMPORAL VARIABILITY; CROP EVAPOTRANSPIRATION; HYDROLOGICAL
   DROUGHT; PAN EVAPORATION}},
Research-Areas = {{Water Resources}},
Web-of-Science-Categories  = {{Water Resources}},
Author-Email = {{ppsunsanlei@126.com}},
ResearcherID-Numbers = {{Chen, Haishan/W-3747-2018}},
ORCID-Numbers = {{Chen, Haishan/0000-0002-2403-3187}},
Funding-Acknowledgement = {{National Key Research and Development Program of China
   {[}2016YFA0600702]; National Natural Science Foundation of ChinaNational
   Natural Science Foundation of China {[}41605042, 41230422, 41625019];
   Natural Science Foundation of Jiangsu Province, ChinaNatural Science
   Foundation of Jiangsu Province {[}BK20151525]; Qinglan Project of
   Jiangsu Province of China; Priority Academic Program Development (PAPD)
   of Jiangsu Higher Education Institutions}},
Funding-Text = {{National Key Research and Development Program of China, Grant/Award
   Number: 2016YFA0600702; National Natural Science Foundation of China,
   Grant/Award Numbers: 41605042, 41230422 and 41625019; Natural Science
   Foundation of Jiangsu Province, China, Grant/Award Number: BK20151525;
   Qinglan Project of Jiangsu Province of China; Priority Academic Program
   Development (PAPD) of Jiangsu Higher Education Institutions}},
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Number-of-Cited-References = {{109}},
Times-Cited = {{6}},
Usage-Count-Last-180-days = {{5}},
Usage-Count-Since-2013 = {{29}},
Journal-ISO = {{Hydrol. Process.}},
Doc-Delivery-Number = {{GR7DV}},
Unique-ID = {{ISI:000442849100008}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000437991600013,
Author = {Li, Jizhe and Huang, Guohe and Liu, Lirong},
Title = {{Ecological network analysis for urban metabolism and carbon emissions
   based on input-output tables: A case study of Guangdong province}},
Journal = {{ECOLOGICAL MODELLING}},
Year = {{2018}},
Volume = {{383}},
Pages = {{118-126}},
Month = {{SEP 10}},
Note = {{20th Biennial Conference of the
   International-Society-for-Ecological-Modelling (ISEM), Towson, MD, MAY
   08-12, 2016}},
Organization = {{Int Soc Ecol Modelling}},
Abstract = {{Global warming has received more and more attention in recent years for
   its inevitable influence on population, species, soil, ocean, water and
   so on. It is essential to investigate the urban metabolism of carbon
   emissions which is a main cause of global warming and most of it occurs
   in the process of production and living in urban areas. In this paper, a
   carbon emission metabolic network is established to explore the emission
   reduction strategies by modeling carbon dioxide flows and identifying
   the mutual relationships based on the input-output analysis.
   Specifically, Eff-Lorenz curve derived from the painting of Lorenz curve
   is developed to compare the efficiency of carbon emissions from
   different sectors. The newly developed method has been applied to
   Guangdong province to demonstrate its availability and benefit. It is
   revealed that carbon emissions mainly concentrated in the secondary and
   tertiary industries with electric power generation, manufacturing
   industry, domestic consumption and transportation ranking at the top.
   The competition relationship reveals good interactions in terms of
   emission reduction while a mutualism relationship provides effective
   pathways to mitigate carbon emissions between pairwise sectors
   simultaneously. In Guangdong province, upgrading the dean combustion
   technology in electric power generation and energy extraction sectors
   would drive other sectors to cut emissions and adjusting the production
   structure of the construction sector also contribute to achieve this
   goal. The results are expected to provide corresponding and holistic
   reference for decision makers to develop the mitigation policies.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article; Proceedings Paper}},
Language = {{English}},
Affiliation = {{Huang, GH (Corresponding Author), North China Elect Power Univ, Inst Energy Environm \& Sustainabil Res, UR NCEPU, Beijing 102206, Peoples R China.
   Li, Jizhe, North China Elect Power Univ, Sino Canada Resources \& Environm Res Acad, Beijing 102206, Peoples R China.
   Huang, Guohe, North China Elect Power Univ, Inst Energy Environm \& Sustainabil Res, UR NCEPU, Beijing 102206, Peoples R China.
   Liu, Lirong, Univ Regina, Inst Energy Environm \& Sustainable Communities, Regina, SK S4S 0A2, Canada.}},
DOI = {{10.1016/j.ecolmodel.2018.05.009}},
ISSN = {{0304-3800}},
EISSN = {{1872-7026}},
Keywords = {{Input-output table; Carbon emission; Urban metabolism; Mitigation;
   Ecological network analysis; Guangdong province}},
Keywords-Plus = {{MODEL DEVELOPMENT; CLIMATE-CHANGE; UNITED-STATES; SYSTEM; CYCLE;
   PERSPECTIVE; SIMULATION; DYNAMICS; CITIES; ENERGY}},
Research-Areas = {{Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Ecology}},
Author-Email = {{huang@iseis.org}},
ResearcherID-Numbers = {{Huang, Guohe/AAA-7305-2019
   Huang, Guohe/H-5306-2011
   }},
ORCID-Numbers = {{Huang, Guohe/0000-0003-4974-3019
   Liu, Lirong/0000-0003-2872-0870}},
Funding-Acknowledgement = {{National Key Research and Development Plan {[}2016YFC0502800,
   2016YFA0601502]; Natural Sciences FoundationNational Natural Science
   Foundation of China {[}51520105013, 51679087]; 111 Program {[}B14008];
   Natural Science and Engineering Research Council of CanadaNatural
   Sciences and Engineering Research Council of Canada}},
Funding-Text = {{This research was supported by the National Key Research and Development
   Plan (2016YFC0502800, 2016YFA0601502), the Natural Sciences Foundation
   (51520105013, 51679087), the 111 Program (B14008) and the Natural
   Science and Engineering Research Council of Canada.}},
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