text:
SRFDP)
   {[}20130003110027]; China-EU Joint Project from Ministry of Science and
   Technology of China {[}SQ2013ZOA000022]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (No. 71573021, 7171101061), Specialized Research Fund for the Doctoral
   Program of Higher Education of China (No. 20130003110027), China-EU
   Joint Project from Ministry of Science and Technology of China (No.
   SQ2013ZOA000022).}},
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   Wang SG, 2018, APPL ENERG, V227, P353, DOI 10.1016/j.apenergy.2017.11.093.
   Wang SG, 2017, APPL ENERG, V196, P208, DOI 10.1016/j.apenergy.2017.02.011.
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Number-of-Cited-References = {{29}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{2}},
Doc-Delivery-Number = {{BM9IL}},
Unique-ID = {{ISI:000470975400049}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000470975400116,
Author = {Gao, Tong and Fang, Delin and Chen, Bin},
Editor = {{Wang, H and Wang, X and Yan, J and Wu, J and Yang, Y and Li, H}},
Title = {{Linkages analysis for water-PM2.5 nexus in Beijing}},
Booktitle = {{CLEANER ENERGY FOR CLEANER CITIES}},
Series = {{Energy Procedia}},
Year = {{2018}},
Volume = {{152}},
Pages = {{725-730}},
Note = {{Applied Energy Symposium and Forum - Low-Carbon Cities and Urban Energy
   Systems (CUE), Shanghai, PEOPLES R CHINA, JUN 05-07, 2018}},
Organization = {{Appl Energy; Appl Energy Innovat Inst; Tongji Univ; China Assoc Sci \&
   Technol, HOME Program; Malardalen Univ, Future Energy Profile; Shanghai
   Key Lab Urban Regenerat \& Spatial Optimizat Technol; MOE Joint Lab Int
   Cooperat Eco Urban Design; Sichuan Univ; Shanghai Univ Electric Power;
   BEEUE; Int Clean Energy Talent Program; UNiLAB}},
Abstract = {{Along with the rapid development of urban economy, the shortage of water
   resources and air pollution are becoming major challenges for
   sustainable urban development. The emission of particulate matter 2.5
   (PM2.5) is strongly associated with industrialization processes, which
   is also intertwined with water utilization processes. Currently, several
   clean air action policies and water conservation policies have been
   issued in China in order to improve the air quality and protect water
   resources, while the connections between these two environmental
   elements are less investigated. In this paper, linkage analysis, which
   descended from input-output analysis, is used to investigate water-PM2.5
   nexus in Beijing. Via analysis of backward linkage and forward linkage,
   the major sectors and pathways associating with water consumption and
   PM2.5 emission are revealed intuitively. We also examined upstream and
   downstream resource flows in the economic network of Beijing, and
   characterized the economic role as well as water consumption and PM2.5
   emission of each sector along the entire supply chain by linkage
   analysis. Copyright (C) 2018 Elsevier Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.
   Gao, Tong, Shandong Normal Univ, Sch Business, Jinan 250358, Shandong, Peoples R China.
   Fang, Delin; Chen, Bin, Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.}},
DOI = {{10.1016/j.egypro.2018.09.236}},
ISSN = {{1876-6102}},
Keywords = {{PM2.5; Linkage analysis; Water-PM25 nexus; Beijing}},
Keywords-Plus = {{SOURCE APPORTIONMENT; POLLUTION; PM2.5}},
Research-Areas = {{Energy \& Fuels; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Energy \& Fuels; Environmental Sciences}},
Author-Email = {{chenb@bnu.edu.cn}},
ResearcherID-Numbers = {{Fang, Delin/D-7617-2015}},
ORCID-Numbers = {{Fang, Delin/0000-0003-0238-328X}},
Funding-Acknowledgement = {{National Key Research \& Development Program {[}2016YFA0602304];
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71573021, 71804014]; Specialized Research Fund
   for the Doctoral Program of Higher Education of ChinaSpecialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   {[}20130003110027]; China-EU Joint Project from Ministry of Science and
   Technology of China {[}SQ2013ZOA000022]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (Nos. 71573021, 71804014), Specialized Research Fund for the Doctoral
   Program of Higher Education of China (No. 20130003110027), and China-EU
   Joint Project from Ministry of Science and Technology of China (No.
   SQ2013ZOA000022).}},
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   Zhang SH, 2015, APPL ENERG, V147, P192, DOI 10.1016/j.apenergy.2015.02.081.}},
Number-of-Cited-References = {{14}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{2}},
Doc-Delivery-Number = {{BM9IL}},
Unique-ID = {{ISI:000470975400116}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000470975400120,
Author = {Duan, Cuncun and Chen, Bin},
Editor = {{Wang, H and Wang, X and Yan, J and Wu, J and Yang, Y and Li, H}},
Title = {{Analysis of global energy consumption inequality by using Lorenz curve}},
Booktitle = {{CLEANER ENERGY FOR CLEANER CITIES}},
Series = {{Energy Procedia}},
Year = {{2018}},
Volume = {{152}},
Pages = {{750-755}},
Note = {{Applied Energy Symposium and Forum - Low-Carbon Cities and Urban Energy
   Systems (CUE), Shanghai, PEOPLES R CHINA, JUN 05-07, 2018}},
Organization = {{Appl Energy; Appl Energy Innovat Inst; Tongji Univ; China Assoc Sci \&
   Technol, HOME Program; Malardalen Univ, Future Energy Profile; Shanghai
   Key Lab Urban Regenerat \& Spatial Optimizat Technol; MOE Joint Lab Int
   Cooperat Eco Urban Design; Sichuan Univ; Shanghai Univ Electric Power;
   BEEUE; Int Clean Energy Talent Program; UNiLAB}},
Abstract = {{It has been proved that carbon emission is highly related to energy
   consumption. Since energy consumption contributes the most of carbon
   emission, studying of global energy consumption will help to figure out
   various positions of different countries du ring the history and
   corresponding responsibilities in reduction of carbon emission which is
   highly relying on the change of energy consumption amount and structure.
   Recent years, developing countries, such as China and India, are going
   to replace the developed countries to become the major energy importers
   and consumers. However, large parts of energy embodied in commodities
   are exported by them to developed countries. From consumer side, the
   terminal of embodied energy, energy consumption trends and energy
   consumption structures among the world are all not clear enough to help
   figure out the responsibilities of different countries. In our study, we
   apply multi-regional input output model (MR10) to measure the embodied
   energy consumption among 121 countries in the world from consumer side.
   Meanwhile, Lorenz curve is also used to quantify and reveal the
   inequality among different countries. The results show that the global
   GINI coefficient is decreasing from 0.602 in 2000 to 0.501 in 2013,
   which implies total energy consumption condition in the world is going
   to be more and more equal from 2000 to 2013. From country side, he US
   locates at the top of the Lorenz curve all over the years, where the
   energy consumption per capita is extremely higher than all the other
   countries. As to global non-renewable energy consumption from 1990 to
   2013, the GINI coefficient is decreasing among all three kinds of
   energy: coal, petroleum, and natural gas. Almost all the developed
   countries and developing countries are more and more relying on coal
   consumption. The GINI coefficient of renewable energy is obviously
   larger than non-renewable energy, which implies a great inequality among
   the world during 1990 in 2013. The potential reason is the huge
   technology gap between developed countries and developing countries.
   Copyright (C) 2018 Elsevier Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.
   Duan, Cuncun; Chen, Bin, Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.}},
DOI = {{10.1016/j.egypro.2018.09.240}},
ISSN = {{1876-6102}},
Keywords = {{Energy inquality; input output analysis; Lorenz curve}},
Keywords-Plus = {{CO2; TRADE}},
Research-Areas = {{Energy \& Fuels; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Energy \& Fuels; Environmental Sciences}},
Author-Email = {{chenb@bnu.edu.cn}},
Funding-Acknowledgement = {{National Key Research \& Development Program {[}2016YFA0602304];
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71573021, 7171101061]; Specialized Research Fund
   for the Doctoral Program of Higher Education of ChinaSpecialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   {[}20130003110027]; China-EU Joint Project from Ministry of Science and
   Technology of China {[}SQ2013ZOA000022]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (No. 71573021, 7171101061), Specialized Research Fund for the Doctoral
   Program of Higher Education of China (No. 20130003110027), China-EU
   Joint Project from Ministry of Science and Technology of China (No.
   SQ2013ZOA000022).}},
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Number-of-Cited-References = {{16}},
Times-Cited = {{2}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{2}},
Doc-Delivery-Number = {{BM9IL}},
Unique-ID = {{ISI:000470975400120}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000470975400150,
Author = {Liu Hongtao and Liu Wenjia},
Editor = {{Wang, H and Wang, X and Yan, J and Wu, J and Yang, Y and Li, H}},
Title = {{The analysis of effects of clean energy power generation}},
Booktitle = {{CLEANER ENERGY FOR CLEANER CITIES}},
Series = {{Energy Procedia}},
Year = {{2018}},
Volume = {{152}},
Pages = {{947-952}},
Note = {{Applied Energy Symposium and Forum - Low-Carbon Cities and Urban Energy
   Systems (CUE), Shanghai, PEOPLES R CHINA, JUN 05-07, 2018}},
Organization = {{Appl Energy; Appl Energy Innovat Inst; Tongji Univ; China Assoc Sci \&
   Technol, HOME Program; Malardalen Univ, Future Energy Profile; Shanghai
   Key Lab Urban Regenerat \& Spatial Optimizat Technol; MOE Joint Lab Int
   Cooperat Eco Urban Design; Sichuan Univ; Shanghai Univ Electric Power;
   BEEUE; Int Clean Energy Talent Program; UNiLAB}},
Abstract = {{As pollution has become a significant issue in China, developing clean
   energy power generation is one of the main strategies to promote the
   sustainable economy. Based on the partially closed input-output model
   corresponding to 29 industries in 2012, this paper categorized power
   generation sectors to coal-fire power generation, gas power generation,
   wind power generation, photovoltaic generation, biomass energy power
   generation, and nuclear power generation to analyze the impacts on
   environment and social-economic developments. The results showed that
   improving single clean energy technology would lead to different degrees
   of positive impacts on environment, but the effects of GDP development
   and employment are highly correlated with the various generating costs.
   For the high generating costs, the clean-energy technologies would
   contribute to the positive effects; however, the drawbacks of social
   economic development could overweight the benefits for the low
   generating costs in short run. In addition, improving diverse clean
   energy generating approaches could promote GDP growth, reduce pollution,
   and increase employment. Finally, this paper provided some policy
   suggestions for the green-energy power supply and low-carbon economic
   developments. Copyright (C) 2018 Elsevier Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Liu, HT (Corresponding Author), Northwestern Polytech Univ, Sch Management, Xian, Shaanxi, Peoples R China.
   Liu Hongtao; Liu Wenjia, Northwestern Polytech Univ, Sch Management, Xian, Shaanxi, Peoples R China.}},
DOI = {{10.1016/j.egypro.2018.09.098}},
ISSN = {{1876-6102}},
Keywords = {{input-output analysis; clean energy power generation; macroeconomic
   effects; environmental effects; China}},
Keywords-Plus = {{RENEWABLE ENERGY; EMPLOYMENT}},
Research-Areas = {{Energy \& Fuels; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Energy \& Fuels; Environmental Sciences}},
Author-Email = {{1048264858@qq.com}},
Cited-References = {{Corona B, 2016, SOL ENERG MAT SOL C, V156, P112, DOI 10.1016/j.solmat.2016.03.014.
   Garrett-Peltier H, 2017, ECON MODEL, V61, P439, DOI 10.1016/j.econmod.2016.11.012.
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Number-of-Cited-References = {{8}},
Times-Cited = {{3}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BM9IL}},
Unique-ID = {{ISI:000470975400150}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000471031800010,
Author = {Wang, Anduo},
Book-Group-Author = {{ACM}},
Title = {{Database Criteria for Network Policy Chain}},
Booktitle = {{PROCEEDINGS OF THE 2018 ACM INTERNATIONAL WORKSHOP ON SECURITY IN
   SOFTWARE DEFINED NETWORKS \& NETWORK FUNCTION VIRTUALIZATION
   (SDN-NFVSEC'18)}},
Year = {{2018}},
Pages = {{49-54}},
Note = {{ACM International Workshop on Security in Software Defined Networks and
   Network Function Virtualization (SDN-NFVSec), Tempe, AZ, MAR 21, 2018}},
Organization = {{Assoc Comp Machinery; ACM SIGSAC}},
Abstract = {{Network policies that offer vital functionalities are often organized in
   a chain. Current practice either assumes proper policy chains as a prior
   or relies on simple syntax-based input-output analysis. This paper
   examines and addresses several difficulties with this approach -
   context-dependent policy interaction, unnecessarily coupled policies,
   and policies that must be jointly examined, proposing database integrity
   constraints as a means towards a semantic-based finer solution. Built on
   a unified logical framework to describe and reason about policy chains,
   our database solution gives (1) criteria that derive correct policy
   chain with a more accurate estimate of policy dependency, and (2)
   criteria that check and obtain atomic policy, unit of policy that is
   proper for policy chain.}},
Publisher = {{ASSOC COMPUTING MACHINERY}},
Address = {{1515 BROADWAY, NEW YORK, NY 10036-9998 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Wang, AD (Corresponding Author), Temple Univ, Philadelphia, PA 19122 USA.
   Wang, Anduo, Temple Univ, Philadelphia, PA 19122 USA.}},
DOI = {{10.1145/3180465.3180471}},
ISBN = {{978-1-4503-5635-0}},
Research-Areas = {{Computer Science}},
Web-of-Science-Categories  = {{Computer Science, Software Engineering; Computer Science, Theory \&
   Methods}},
Author-Email = {{adw@temple.edu}},
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Number-of-Cited-References = {{27}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BM9JM}},
Unique-ID = {{ISI:000471031800010}},
DA = {{2020-08-06}},
}

@incollection{ ISI:000467330600008,
Author = {Tukker, Arnold and Vivanco, David Font},
Editor = {{Bleischwitz, R and Hoff, H and Spataru, C and VanDerVoet, E and VanDeveer, SD}},
Title = {{INPUT-OUTPUT ANALYSIS AND RESOURCE NEXUS ASSESSMENT}},
Booktitle = {{ROUTLEDGE HANDBOOK OF THE RESOURCE NEXUS}},
Series = {{Routledge Handbooks}},
Year = {{2018}},
Pages = {{105-128}},
Publisher = {{ROUTLEDGE}},
Address = {{2 PARK SQ, MILTON PARK, ABINGDON OX14 4RN, OXFORD, ENGLAND}},
Type = {{Article; Book Chapter}},
Language = {{English}},
Affiliation = {{Tukker, A (Corresponding Author), Leiden Univ, Ind Ecol, Leiden, Netherlands.
   Tukker, A (Corresponding Author), Leiden Univ, Inst Environm Sci CML, Leiden, Netherlands.
   Tukker, A (Corresponding Author), Netherlands Org Appl Sci Res TNO, The Hague, Netherlands.
   Tukker, Arnold, Leiden Univ, Ind Ecol, Leiden, Netherlands.
   Tukker, Arnold, Leiden Univ, Inst Environm Sci CML, Leiden, Netherlands.
   Tukker, Arnold, Netherlands Org Appl Sci Res TNO, The Hague, Netherlands.
   Vivanco, David Font, UCL, Inst Sustainable Resources, London, England.
   Vivanco, David Font, Yale Univ, Ctr Ind Ecol, New Haven, CT USA.}},
ISBN = {{978-1-315-56062-5; 978-1-138-67549-0}},
Keywords-Plus = {{ENERGY-WATER NEXUS; INTERNATIONAL-TRADE; SUPPLY SCENARIOS; CONSUMPTION;
   CHINA; TABLES; FOOTPRINTS; EMISSIONS; IMPACTS; LAND}},
Research-Areas = {{Agriculture; Development Studies; Science \& Technology - Other Topics;
   Environmental Sciences \& Ecology; Social Sciences - Other Topics}},
Web-of-Science-Categories  = {{Agricultural Economics \& Policy; Development Studies; Green \&
   Sustainable Science \& Technology; Environmental Sciences; Environmental
   Studies; Social Sciences, Interdisciplinary}},
ResearcherID-Numbers = {{Tukker, Arnold/M-4596-2013}},
ORCID-Numbers = {{Tukker, Arnold/0000-0002-8229-2929}},
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Number-of-Cited-References = {{38}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{0}},
Doc-Delivery-Number = {{BM6RY}},
Unique-ID = {{ISI:000467330600008}},
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@inproceedings{ ISI:000467867600131,
Author = {Wang, C. and Wang, W. and Qu, S. and Li, F. and Liu, S. and Ni, L. D.},
Editor = {{Li, P}},
Title = {{Macroeconomic water resources input-output analysis in Shandong Province}},
Booktitle = {{4TH INTERNATIONAL CONFERENCE ON WATER RESOURCE AND ENVIRONMENT (WRE
   2018)}},
Series = {{IOP Conference Series-Earth and Environmental Science}},
Year = {{2018}},
Volume = {{191}},
Note = {{4th International Conference on Water Resource and Environment (WRE), I
   Shou Univ, Kaohsiung, TAIWAN, JUL 17-21, 2018}},
Abstract = {{The allocation of water resources is linked to economic conditions, and
   the input-output analysis methods of macroeconomic water are applied to
   analyse the macroeconomic impact of water resources on Shandong
   Province. By calculating the input and output coefficients of water
   resources in 14 industries in Shandong Province, the water use
   conditions and water use efficiency of various industry sectors in the
   production process are analysed to provide the basis for the optimal
   allocation of water resources in Shandong Province. After data analysis,
   the following conclusions have been drawn. The direct water consumption
   coefficients for agriculture, power, paper, and petroleum industries are
   relatively large, while the total water consumption coefficients for
   agriculture, food, textile, and paper industries are relatively large.
   The food, textile, and engineering industries have higher water
   consumption multipliers. From 1997 to 2007, the direct and indirect
   water consumption of all industries showed a downward trend, which is
   closely related to the water saving policy. It should be advocated to
   export products with high benefit and low water consumption and import
   agricultural and industrial products for alleviating pressure of water
   shortages by trade forms. In addition, using the added value and water
   consumption of all industry sectors evaluates the production efficiency,
   which plays an important assistance in water resources allocation and
   planning.}},
Publisher = {{IOP PUBLISHING LTD}},
Address = {{DIRAC HOUSE, TEMPLE BACK, BRISTOL BS1 6BE, ENGLAND}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Wang, C (Corresponding Author), Univ Jinan, Sch Water Conservancy \& Environm, Jinan, Shandong, Peoples R China.
   Wang, C.; Qu, S.; Li, F.; Liu, S.; Ni, L. D., Univ Jinan, Sch Water Conservancy \& Environm, Jinan, Shandong, Peoples R China.
   Wang, W., Qingdao Water Divers Yellow River Corp Ltd, Qingdao, Shandong, Peoples R China.}},
DOI = {{10.1088/1755-1315/191/1/012131}},
Article-Number = {{UNSP 012131}},
ISSN = {{1755-1307}},
Research-Areas = {{Environmental Sciences \& Ecology; Water Resources}},
Web-of-Science-Categories  = {{Environmental Sciences; Environmental Studies; Water Resources}},
Author-Email = {{stu\_wangwp@ujn.edu.cn}},
Funding-Acknowledgement = {{Shandong Provincial Natural Science FoundationNatural Science Foundation
   of Shandong Province {[}ZR2016DM13]}},
Funding-Text = {{This study was supported by the Shandong Provincial Natural Science
   Foundation (ZR2016DM13).}},
Cited-References = {{Liu X L, 2003, J EC WATER RESOUR, V21, P35.
   Liu Y Y, 2003, MODERN WATER NETWORK, P136.
   {[}马忠玉 Ma Zhongyu], 2006, {[}生态环境, Ecology and Environment], V15, P416.
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   Wu J S, 2002, MODERN WATER RESOURC, P160.
   Xu J, 2003, ADV SCI TECHNOLOGY W, V23, P17.
   Zhao J M, 2007, THESIS.}},
Number-of-Cited-References = {{14}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{1}},
Journal-ISO = {{IOP Conf. Ser. Earth Envir. Sci.}},
Doc-Delivery-Number = {{BM7GP}},
Unique-ID = {{ISI:000467867600131}},
OA = {{Bronze}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900124,
Author = {Cao, Tao and Wang, Saige and Chen, Bin},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Priority in Energy-water Nexus Based on Input-output Analysis: A Case
   Study of China}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Energy shortage and water crisis are increasingly becoming the major
   constraints for sustainability. The energy-water nexus management are
   facing the problems how to prioritize the energy saving or water saving
   issues for socio-economic production and consumption process. This study
   built the framework to assess the nexus priority issues to identify the
   regional critical nexus issues and critical inter-regional trade pathway
   for nexus management. Here, the priority for energy-water nexus means
   energy-saving or water saving who should be put ahead or who is more
   important aspect for nexus management. Using the input-output analysis
   (10A), we analyzed the embodied EW flows and regional consumption
   behaviors from production perspective. Combining the regional
   energy/water (EVV) consumption and EW resource endowment, we built the
   EW stress index to compare the EW crisis and identify the resource
   saving aspect priority considering the bilateral EW resource endowment.
   The results showed that embodied EW transfer did not bring significant
   change to the local resource stress index. North China should serve as
   consumers while South China as suppliers according to the water priority
   degree distribution. East and Central China with lower energy priority
   degree easily get local energy outflowed which is a severe challenge for
   local energy resource system. By prioritizing the EW regions and
   regional trade, we aim to provide the detail strategy and guidance for
   nexus management.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, State Key Joint Lab Environm Simulat \& Pollut Con, Sch Environm, Beijing 100875, Peoples R China.
   Cao, Tao; Wang, Saige; Chen, Bin, Beijing Normal Univ, State Key Joint Lab Environm Simulat \& Pollut Con, Sch Environm, Beijing 100875, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{Water-energy nexus; water stress index; energy stress index; priority
   degree; China; resource management}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Key Research \& Development Program {[}2016YFA0602304];
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71573021, 7171101061]; Specialized Research Fund
   for the Doctoral Program of Higher Education of ChinaSpecialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   {[}20130003110027]; China-EU Joint Project from Ministry of Science and
   Technology of China {[}SQ2013ZOA000022]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (No. 71573021, 7171101061), Specialized Research Fund for the Doctoral
   Program of Higher Education of China (No. 20130003110027), China-EU
   Joint Project from Ministry of Science and Technology of China (No.
   SQ2013ZOA000022).}},
Cited-References = {{Cabrera E, 2010, J WATER RES PLAN MAN, V136, P669, DOI 10.1061/(ASCE)WR.1943-5452.0000077.
   Carrico N, 2014, J WATER SUPPLY RES T, V63, P342, DOI 10.2166/aqua.2014.094.
   Chen S, 2016, APPL ENERGY.
   Chen SQ, 2015, APPL ENERG, V138, P99, DOI 10.1016/j.apenergy.2014.10.055.
   Feng K, 2014, RENEW SUST ENERG REV, V39, P342, DOI 10.1016/j.rser.2014.07.080.
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   Hoff H., 2011, UNDERSTANDING NEXUS.
   Hussey K, 2012, ECOL SOC, V17, DOI 10.5751/ES-04641-170131.
   Kenway SJ, 2011, WATER SCI TECHNOL, V63, P1983, DOI 10.2166/wst.2011.070.
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   STILLWELL ASHLYNN S, 2009, ENERGY WATER NEXUS T.
   U.S. Department of Energy, 2014, WAT EN NEX CHALL OPP.
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   Zhang XD, 2016, APPL ENERG, V183, P77, DOI 10.1016/j.apenergy.2016.08.156.}},
Number-of-Cited-References = {{17}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{5}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900124}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900137,
Author = {Duan, Cuncun and Chen, Bin},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Land-water Nexus at Urban Scale}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Land and water are two of fundamental resources to maintain basic
   function of urban area. The consumption process of them are twisted
   together (water production needs equipment to filter raw water, and
   treat wastewater, agriculture land needs water to grow grain, etc.).
   Most current nexus studies are focusing on specific project or process.
   However, unveiling the pathway and destination of land use and water
   consumption is also important to instruct the development of city area,
   and to manage and save these two resources synergistically. This study
   applied environment input output analysis to measure the water and land
   consumption in a city in China, meanwhile the nexus relationship is also
   quantified to better understand how these two resources influence each
   other and further affect the industry supply chain in the city. The
   results showed that the agriculture is the most crucial economic sector
   to take land and water synergistical management, especially the
   production of oil seeds and corn. Besides, the Leasing and Business
   Services, and Residential Services and Other Services industries, the
   Food and Tobacco Processing and Water Conservancy, Environment and
   Public Facilities Management industry are also sensitive industries to
   implement water and land synergistical management.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.
   Duan, Cuncun; Chen, Bin, Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{Input-output analysis; embodied water; land use; land-water nexus}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Key Research \& Development Program {[}2016YFA0602304];
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}7153021, 7171101061]; Specialized Research Fund
   for the Doctoral Program of Higher Education of ChinaSpecialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   {[}20130003110027]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (No. 71573021), Specialized Research Fund for the Doctoral Program of
   Higher Education of China (No. 20130003110027), and National Natural
   Science Foundation of China (Nos. 7153021, 7171101061).}},
Cited-References = {{Chen B, 2018, SCI TOTAL ENVIRON, V613, P931, DOI 10.1016/j.scitotenv.2017.09.138.
   Chen SQ, 2015, APPL ENERG, V138, P99, DOI 10.1016/j.apenergy.2014.10.055.
   de Mello K, 2018, CATENA, V167, P130, DOI 10.1016/j.catena.2018.04.027.
   Feng KS, 2011, ECON SYST RES, V23, P371, DOI 10.1080/09535314.2011.638276.
   Klaus H., 2001, Structural Change and Economic Dynamics, V12, P367.
   Li X, 2018, ECOL MODEL, V390, P40, DOI 10.1016/j.ecolmodel.2018.10.016.
   Liu YT, 2019, ECOL INDIC, V97, P466, DOI 10.1016/j.ecolind.2018.10.042.
   Rodriguez RD, 2018, APPL ENERG, V231, P1330, DOI 10.1016/j.apenergy.2018.09.121.
   Silalertruksa T, 2018, J CLEAN PROD, V182, P521, DOI 10.1016/j.jclepro.2018.02.085.}},
Number-of-Cited-References = {{9}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{0}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900137}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900141,
Author = {Jin, Pengfei and Fang, Delin and Chen, Bin},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Accounting the Virtual Water and Virtual Land Based on Input-output
   analysis-A Case Study of Zhangye City}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Water and land are the basic elements of ecological protection, economic
   development and human life in Zhangye city. The virtual water and
   virtual land accounting are the core research content to achieve
   sustainable development in this area. In this paper, the virtual trade
   of water and land in Zhangye city is analyzed via environmental
   input-output analysis. It is found that the virtual water and land in
   this area are in a net outflow state. From the perspective of sectors,
   the agricultural sector is the largest net outflow sector of virtual
   water and virtual land, while the manufacturing sector is the net inflow
   sector. The accounting in this paper can provide a solid foundation for
   the formulation of industrial and trade policies.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Jin, PF (Corresponding Author), Beijing Normal Univ, State Key Lab Water Environm Simulat, Sch Environm, 19 Xinjiekouwai St, Beijing 100875, Peoples R China.
   Jin, Pengfei; Fang, Delin; Chen, Bin, Beijing Normal Univ, State Key Lab Water Environm Simulat, Sch Environm, 19 Xinjiekouwai St, Beijing 100875, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{virtual water; virtual land; input-output analysis}},
Keywords-Plus = {{ENERGY; NEXUS; CHINA}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Science Fund for Distinguished Young Scholars of ChinaNational
   Natural Science Foundation of ChinaNational Science Fund for
   Distinguished Young Scholars {[}71725005]; National Key Research \&
   Development Program {[}2016YFA0602304]; National Natural Science
   Foundation of ChinaNational Natural Science Foundation of China
   {[}71573021, 71628301]}},
Funding-Text = {{This work was supported by the National Science Fund for Distinguished
   Young Scholars of China (71725005), National Key Research \& Development
   Program (2016YFA0602304), and National Natural Science Foundation of
   China (Nos. 71573021, 71628301).}},
Cited-References = {{Chen B, 2018, SCI TOTAL ENVIRON, V613, P931, DOI 10.1016/j.scitotenv.2017.09.138.
   Chen WM, 2017, SCI TOTAL ENVIRON, V584, P990, DOI 10.1016/j.scitotenv.2017.01.152.
   Chen WM, 2017, ECOL INDIC, V74, P321, DOI 10.1016/j.ecolind.2016.11.037.
   Fang DL, 2017, APPL ENERG, V189, P770, DOI 10.1016/j.apenergy.2016.04.020.
   Ramaswami A, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa5556.
   Vorosmarty CJ, 2015, SCIENCE, V349, P478, DOI 10.1126/science.aac6009.
   Vora N, 2017, ACS SUSTAINABLE CHEM, V5.
   Wang SG, 2018, APPL ENERG, V227, P353, DOI 10.1016/j.apenergy.2017.11.093.
   Wu PT, 2016, J AGR ENG, V32, P1.
   Xiang Xue-min, 2006, Journal of Dalian University of Technology, V46, P179.
   {[}邹君 Zou Jun], 2010, {[}中国生态农业学报, Chinese Journal of Eco-Agriculture], V18, P185.}},
Number-of-Cited-References = {{11}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{3}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900141}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900122,
Author = {Liu, Yating and Wang, Saige and Chen, Bin},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Water-land Scarcity Risk Nexus in the National Trade System Based on
   Multiregional Input-output and Ecological Network Analyses}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Massive amounts of water and land are exploited for rapid economic
   development. The increasing demand on water and land has aggravated
   water and land scarcity, which are posing a great risk to national
   economy. In this study, we proposed a network-based scarcity risk
   assessment framework for water-land nexus in national trade system to
   investigate the vulnerability of the national economy to water and land
   scarcity. Based on the hydrological availability of water resource and
   water consumption, the water stress index was first built to assess
   water scarcity in each region. Similarly, based on regional land use and
   land resource, regional land stress index was built. Taking the stress
   index as initial risk, combing with the economic multiregional
   input-output analysis, and the information network model in ecological
   network analysis (ENA), the water-land scarcity risk network was
   established. Finally, a case study was conducted in China to quantify
   the water-land scarcity risk propagation among different regions and
   sectors, concerning both direct risk and integral risk, in the national
   trade system. The results showed that disparities of regional water and
   land use are obvious due to the different natural endowment of water and
   land resources. Most studied provinces had at least slight land stress.
   There are significant differences between initial risk and integral risk
   due to network amplification effect and nexus impact. The proposed
   network-based scarcity risk framework for water-land nexus can identify
   vulnerable provinces and sectors in the national trade network to
   strengthen the resilience of the national economy.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, State Key Joint Lab Environm Simulat \& Pollut Con, Sch Environm, Beijing 100875, Peoples R China.
   Liu, Yating; Wang, Saige; Chen, Bin, Beijing Normal Univ, State Key Joint Lab Environm Simulat \& Pollut Con, Sch Environm, Beijing 100875, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{Multiregional input-output analysis; Ecological network analysis; Water
   and land stress index; Risk assessment; Water-land nexus}},
Keywords-Plus = {{ENVIRONMENTAL IMPACTS; CONSUMPTION; INDICATORS; STRESS}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Key Research \& Development Program {[}2016YFA0602304];
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71573021, 7171101061]; Specialized Research Fund
   for the Doctoral Program of Higher Education of ChinaSpecialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   {[}20130003110027]; China-EU Joint Project from Ministry of Science and
   Technology of China {[}SQ2013ZOA000022]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (No. 71573021, 7171101061), Specialized Research Fund for the Doctoral
   Program of Higher Education of China (No. 20130003110027), China-EU
   Joint Project from Ministry of Science and Technology of China (No.
   SQ2013ZOA000022).}},
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Number-of-Cited-References = {{21}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900122}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900133,
Author = {Wang, Saige and Yang, Qing and Chen, Bin},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{The Synergetic Role of Solar PV in the Unit Commitent of Energy-water
   Nexus}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{China is the biggest solar PV power development country, most of its
   solar PV are located at western areas, with serious water shortage. The
   water shortage has proposed great challenge to energy development, solar
   power as a water-saving renewable energy create the chance to break
   water bottleneck for energy sector. This paper investigated the direct
   water consumption for solar PV from whole life cycle perspective and the
   indirect water embodied in the material, labor and goods were calculated
   based on the input-output analysis. Comparing the water intensity of
   solar PV power with other types energy, we quantified the water saved
   from the solar PV for different regions. The results showed that the
   water intensity for solar PV is 0.692 liter/kWh, and about 46.29\% of
   which are used for material solar grade silicon and solar cells. In
   2014, the water saved due to the solar PV in China had reached 1393 E+8
   L. Among them, Qinghai, Gansu, Xinjiang, Ningxia and Inner Mongolia are
   top five provinces with the highest water saving, saving water with 671
   E+8 L, 246 E+8 L, 156 E+8 L, 65.2 E+8 L and 59.7 E+8 L, respectively,
   which accounting for 85.94\% of the national saved water. By
   investigating the water intensity and provincial water saved due to
   solar PV, we aimed to provide insights for the solar PV development.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.
   Wang, Saige; Chen, Bin, Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.
   Yang, Qing, Huazhong Univ Sci Technol, China EU Inst Clean \& Renewable Energy, Wuhan 430070, Hubei, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{Energy-water nexus; solar PV; regional renewable energy development;
   life cycle analysis}},
Keywords-Plus = {{INPUT-OUTPUT}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Key Research \& Development Program {[}2016YFA0602304];
   National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71573021, 7171101061]; Specialized Research Fund
   for the Doctoral Program of Higher Education of ChinaSpecialized
   Research Fund for the Doctoral Program of Higher Education (SRFDP)
   {[}20130003110027]; China-EU Joint Project from Ministry of Science and
   Technology of China {[}SQ2013ZOA000022]}},
Funding-Text = {{This work was supported by the National Key Research \& Development
   Program (2016YFA0602304), National Natural Science Foundation of China
   (No. 71573021, 7171101061), Specialized Research Fund for the Doctoral
   Program of Higher Education of China (No. 20130003110027), China-EU
   Joint Project from Ministry of Science and Technology of China (No.
   SQ2013ZOA000022).}},
Cited-References = {{Feng K, 2014, RENEW SUST ENERG REV, V39, P342, DOI 10.1016/j.rser.2014.07.080.
   Guo MY, 2016, RENEW SUST ENERG REV, V66, P742, DOI 10.1016/j.rser.2016.08.026.
   HENDRICKSON C, 1998, EC INPUT OUTPUT MODE.
   Liu LQ, 2010, RENEW SUST ENERG REV, V14, P301, DOI 10.1016/j.rser.2009.08.005.
   Macknick J, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/4/045803.
   Pfister S., 2011, ENV EVALUATION FRESH.
   Solangi KH, 2011, PRESENT SOLAR ENERGY, V4.
   Tan D, WATER ENERGY SECURE.
   Torcellini P, 2003, CONSUMPTIVE WATER US, DOI {[}10.2172/15005918, DOI 10.2172/15005918].
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   Wang SG, 2018, APPL ENERG, V227, P353, DOI 10.1016/j.apenergy.2017.11.093.
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   Wu XD, 2017, APPL ENERG, V195, P125, DOI 10.1016/j.apenergy.2017.03.029.}},
Number-of-Cited-References = {{15}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{0}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900133}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900139,
Author = {Yang, Jin and Song, Dan and Wu, Feng},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Consumption-based PM2.5 Emission Accounting of Beijing}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Beijing, the capital of China was severely affected by large scale haze
   in recent years. As the major contributor of haze, PM2.5 emission should
   be paid utmost attention. To respond to the call of PM2.5 emissions
   mitigation, an efficient accounting framework should be proposed.
   Traditional narrowly defined production-based inventory that consider
   the direct emissions from native energy consumption may generally lead
   to underestimates of the emissions derived from providing products and
   services. To comprehensively evaluate the supply-chain PM2.5 emissions
   of Beijing, by using the regional emission inventory and environmentally
   extended input output framework, a consumption-based PM2.5 emission
   accounting model was employed in this study. The results show that PM2.5
   emission from direct residential consumption still constitutes 44.48\%
   of total emission in 2015 due to the combustion of coal in rural areas.
   Capital formation constitutes the largest proportion of
   consumption-based PM2.5 emission. It is expected that the study will
   bring new insights for PM2.5 emissions mitigation actions as well as
   enlarging the possibilities for future environmental policies for
   Beijing, or even other global cities fighting against the air pollution.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Song, D (Corresponding Author), China Natl Inst Standardizat, Resource \& Environm Branch, Beijing 100191, Peoples R China.
   Yang, Jin, China Univ Geosci, Sch Econ \& Management, Beijing 100083, Peoples R China.
   Song, Dan, China Natl Inst Standardizat, Resource \& Environm Branch, Beijing 100191, Peoples R China.
   Wu, Feng, Chinese Acad Sci, Inst Geog Sci \& Nat Resources Res, Ctr Chinese Agr Policy, Beijing 100101, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{PM2.5 emission; consumption-based emission; Input-output analysis;
   Beijing}},
Keywords-Plus = {{WATER FOOTPRINT; TRADE; CO2}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{MOE (Ministry of Education in China) Project of Humanities and Social
   Sciences {[}17YJC790187]; National Natural Science Foundation of
   ChinaNational Natural Science Foundation of China {[}71704164]}},
Funding-Text = {{This research was financially supported by the MOE (Ministry of
   Education in China) Project of Humanities and Social Sciences (No.
   17YJC790187) and the National Natural Science Foundation of China (No.
   71704164),.}},
Cited-References = {{Dong HJ, 2013, SCI TOTAL ENVIRON, V442, P215, DOI 10.1016/j.scitotenv.2012.10.049.
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Number-of-Cited-References = {{14}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{0}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900139}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900136,
Author = {Yang, Weisi and Fang, Delin and Chen, Bin},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Interregional Water-carbon Nexus Control Pathway in
   Beijing-Tianjin-Hebei}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Water scarcity and heavy carbon emission are two main environmental
   problems in Beijing-Tianjin-Hebei area. Water resources are consumed in
   inter-regional trade while carbon emissions are generated and
   transferred across various industrial sectors and even regions via
   supply chains. In this study, we employ the Multi-regional Input-output
   (MRIO) approach to model both water and carbon flows embodied in the
   interregional system. The network control analysis (NCA) originated from
   ecological network analysis is combined with MRIO to determine major
   control pathways across the concerned regions. As a result, key control
   pathways via the specific sectors are identified. The results show that,
   considering water consumption, prominent water control pathways are
   mainly located in Hebei province, of which, the top one is Hebei's
   agriculture sector controlling its light manufacturing sector with
   1.13x10(3) million m(3), followed by Hebei's Heavy Manufacturing sector
   controlling its Construction sector with 5.38x10(2) million m(3). In
   Beijing and Tianjin, local Heavy Manufacturing sector and Construction
   sector are considered as notable control pathways. On the other hand,
   regarding carbon emissions, the most significant control pathway is
   Heavy Manufacturing sector controlling construction sector in Hebei.
   Also, Electricity and water supply sector in Hebei owns several
   prominent control pathways with Construction sector, Manufacturing
   sector and Service sector. In Beijing and Tianjin, major control
   pathways are Electricity sector controlling Service sector and
   Manufacturing sector controlling Construction sector. This study may
   provide a framework to identify control pathways on water consumption
   and carbon emission and formulate polices with clear control objectives
   and paths for Beijing Tianjin-Hebei area.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Chen, B (Corresponding Author), Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.
   Yang, Weisi; Fang, Delin; Chen, Bin, Beijing Normal Univ, Sch Environm, State Key Joint Lab Environm Simulat \& Pollut Con, Beijing 100875, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{Control pathway; water consumption; carbon emission; Multi-regional
   Input-output analysis; Network control analysis}},
Keywords-Plus = {{ECOLOGICAL NETWORK; METABOLISM; EMISSIONS}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Science Fund for Distinguished Young Scholars of ChinaNational
   Natural Science Foundation of ChinaNational Science Fund for
   Distinguished Young Scholars {[}71725005]; Strategic Priority Research
   Program of Chinese Academy of SciencesChinese Academy of Sciences
   {[}XDA20100104]; National Natural Science Foundation of ChinaNational
   Natural Science Foundation of China {[}71573021, 7171101061]}},
Funding-Text = {{This work was supported by the National Science Fund for Distinguished
   Young Scholars of China (71725005), Strategic Priority Research Program
   of Chinese Academy of Sciences (No. XDA20100104), and National Natural
   Science Foundation of China (Nos. 71573021, 7171101061).}},
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Number-of-Cited-References = {{16}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{1}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900136}},
DA = {{2020-08-06}},
}

@inproceedings{ ISI:000468631900127,
Author = {Zhang, Yiyi and Chen, Qingtong and Zheng, Hanbo and Chen, Bin and Liu,
   Jiefeng and Wang, Jiaqi},
Book-Group-Author = {{Destech Publicat Inc}},
Title = {{Identifying Electric Power Demand in Structural Path Analysis: A Case
   Study of 30 Chinese Provinces}},
Booktitle = {{JOINT INTERNATIONAL CONFERENCE ON ENERGY, ECOLOGY AND ENVIRONMENT ICEEE
   2018 AND ELECTRIC AND INTELLIGENT VEHICLES ICEIV 2018}},
Series = {{DEStech Transactions on Environment Energy and Earth Sciences}},
Year = {{2018}},
Note = {{International Conference on Energy, Ecology and Environment (ICEEE) /
   International Conference on Electric and Intelligent Vehicles (ICEIV),
   Swinburne Univ Technol, Melbourne, AUSTRALIA, NOV 21-25, 2018}},
Organization = {{Beijing Normal Univ; Beijing Inst Technol; Shandong Univ; Adv Energy
   Storage \& Applicat; OFT Energy Res}},
Abstract = {{Electricity demand is inseparable from resources, environment,and social
   and economic development. However, the traditional study of electricity
   consumption cannot effectively explore the indirect power consumption
   that may be hidden in the supply chain of the whole industry. Therefore,
   this study adopts a structural path analysis method to connect the whole
   supply chain of China's social economy with the final consumption of
   various industries, which can excavate the indirect power consumption in
   the supply chain.The main work is as follows: 1) Set up a national
   regional input-output model based on supply chain, and the model removed
   imports on the influence of various industries. 2) Analyze the final
   demand impact on electricity consumption. 3) Tracking the consumption of
   electricity through the domestic supply chain. This method is applied to
   30 provinces (total 900 industries) in China, this method was applied to
   30 provinces (total 900 industries) in China, and the result analysis
   showed that ``Fix capital formation - Shandong's construction Shandong's
   Metallurgy{''} was the maximum path of power consumption, which proved
   that the proposed method can effectively track the indirect consumption
   of the electric power.}},
Publisher = {{DESTECH PUBLICATIONS, INC}},
Address = {{439 DUKE STREET, LANCASTER, PA 17602-4967 USA}},
Type = {{Proceedings Paper}},
Language = {{English}},
Affiliation = {{Zheng, HB (Corresponding Author), Guangxi Univ, Guangxi Key Lab Power Syst Optimizat \& Energy Tec, Nanning 530004, Guangxi, Peoples R China.
   Chen, B (Corresponding Author), Peking Univ, Coll Engn, Lab Syst Ecol \& Sustainabil Sci, Beijing 100871, Peoples R China.
   Zhang, Yiyi; Chen, Qingtong; Zheng, Hanbo; Liu, Jiefeng; Wang, Jiaqi, Guangxi Univ, Guangxi Key Lab Power Syst Optimizat \& Energy Tec, Nanning 530004, Guangxi, Peoples R China.
   Chen, Bin, Peking Univ, Coll Engn, Lab Syst Ecol \& Sustainabil Sci, Beijing 100871, Peoples R China.}},
ISSN = {{2475-8833}},
ISBN = {{978-1-60595-590-2}},
Keywords = {{Embodied electric power use; Input-output analysis; Structural path
   analysis; Domestic supply chain; Chinese economy}},
Keywords-Plus = {{RENEWABLE ENERGY; MATRIX}},
Research-Areas = {{Energy \& Fuels; Transportation}},
Web-of-Science-Categories  = {{Energy \& Fuels; Transportation Science \& Technology}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}51867003]; National Basic Research Program of
   China (973 Program)National Basic Research Program of China
   {[}2013CB228205]; National High-tech R\&D Program of China (863 Program)
   {[}2015AA050204]; Natural Science Foundation of GuangxiNational Natural
   Science Foundation of Guangxi Province {[}2015GXNSFBA139235]; Foundation
   of Guangxi Science and Technology Department {[}AE020069]; Foundation of
   Guangxi Education Department {[}T3020097903]; National Key Research and
   Development Program of China {[}2016YFB0900101]; school of electrical
   engineering of Guangxi university; school of environment of Beijing
   normal university}},
Funding-Text = {{The authors acknowledge the National Natural Science Foundation of China
   (Grant No. 51867003), the National Basic Research Program of China (973
   Program, 2013CB228205), the National High-tech R\&D Program of China
   (863 Program, 2015AA050204), the Natural Science Foundation of Guangxi
   (2015GXNSFBA139235), the Foundation of Guangxi Science and Technology
   Department (AE020069), the Foundation of Guangxi Education Department
   (T3020097903), and the National Key Research and Development Program of
   China (2016YFB0900101) in support of this work. This study was supported
   by the school of electrical engineering of Guangxi university and the
   school of environment of Beijing normal university, and sincerely thank
   associate professor yiyi,zhang and doctor bin,chen.}},
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Number-of-Cited-References = {{15}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{2}},
Doc-Delivery-Number = {{BM7ZY}},
Unique-ID = {{ISI:000468631900127}},
DA = {{2020-08-06}},
}

@article{ ISI:000468007700048,
Author = {Abid, Muhammad Adnan and Almazroui, Mansour and Kucharski, Fred and
   O'Brien, Enda and Yousef, Ahmed Elsayed},
Title = {{ENSO relationship to summer rainfall variability and its potential
   predictability over Arabian Peninsula region}},
Journal = {{NPJ CLIMATE AND ATMOSPHERIC SCIENCE}},
Year = {{2018}},
Volume = {{1}},
Abstract = {{The El Nino Southern Oscillation (ENSO) phenomenon is considered to be
   responsible for rainfall predictability in many regions. Some of its
   regional teleconnections, such as over the Arabian Peninsula in boreal
   summer (June-August) season, are not well studied. Therefore, in this
   paper, the relationship between the summer seasonal mean rainfall and
   ENSO is analyzed with the aid of a 15-member ensemble of simulations
   using the Saudi-King Abdulaziz University (KAU) Atmospheric Global
   Climate Model (AGCM) for the period 1981-2015. The southwestern
   peninsula rainfall is linked to the Sea Surface Temperature (SST)
   anomalies in the central-eastern pacific region. This relationship is
   established through an atmospheric teleconnection which shows
   upper-level convergence anomalies over the southern Arabian Peninsula
   compensating the central-eastern Pacific upper-level divergence
   anomalies for the warm ENSO phase, and vice-versa for the cold Phase.
   The upper-level convergence over the southern Arabian Peninsula leads to
   sinking motion, low-level divergence and consequently to reduced
   rainfall in the warm phase, while reverse happens in the cold phase. The
   correlation coefficient between the observed area-averged Nino3.4 index
   and a Southwestern Arabian Peninsula Rainfall Index (SARI) is -0.43
   (statistically significant at 95\%). Overall, model shows a potential
   predictability (PP) of 0.53 for the SARI region. Predictability during
   El Nino is higher than during La Nina events. This is not only because
   of a stronger signal, but also noise reduction contributes to the
   increase of PP in El Nino compared to that of La Nina years.}},
Publisher = {{NATURE PUBLISHING GROUP}},
Address = {{MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Abid, MA (Corresponding Author), King Abdulaziz Univ, Dept Meteorol, Ctr Excellence Climate Change Res, Jeddah, Saudi Arabia.
   Abid, Muhammad Adnan; Almazroui, Mansour; Kucharski, Fred; O'Brien, Enda; Yousef, Ahmed Elsayed, King Abdulaziz Univ, Dept Meteorol, Ctr Excellence Climate Change Res, Jeddah, Saudi Arabia.
   Kucharski, Fred, Abdus Salam Int Ctr Theoret Phys ICTP, Earth Syst Phys Sect, Trieste, Italy.}},
DOI = {{10.1038/s41612-017-0003-7}},
Article-Number = {{20171}},
ISSN = {{2397-3722}},
Keywords-Plus = {{INDIAN MONSOON; EL-NINO; CLIMATE; PRECIPITATION; ENSEMBLE; GCM; PACIFIC;
   MODEL}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{mabid@kau.edu.sa}},
ResearcherID-Numbers = {{Abid, Muhammad Adnan/L-1845-2013}},
ORCID-Numbers = {{Abid, Muhammad Adnan/0000-0002-7389-7977}},
Funding-Acknowledgement = {{Center of the Excellence for Climate Change Research (CECCR); Deanship
   of the Graduate Studies (DGS); Deanship of the Scientific Research, King
   Abdulaziz University (KAU), Jeddah, Saudi Arabia}},
Funding-Text = {{The authors would like to thank the Director of the Center of the
   Excellence for Climate Change Research (CECCR), Deanship of the Graduate
   Studies (DGS) and the Deanship of the Scientific Research, King
   Abdulaziz University (KAU), Jeddah, Saudi Arabia for providing necessary
   support for this work. We would also like to thank the KAU High
   Performance Computing (HPC) Center (http://hpc.kau.edu.sa) for providing
   the Aziz Supercomputer as a computational resource for the current
   research work. The authors thank Franco Molteni for the ECMWF-SYS4
   dataset. The authors would like to thank Editors (Chief and associate),
   the two anonymous reviewers for their useful suggestions that have
   improved the manuscript.}},
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Number-of-Cited-References = {{47}},
Times-Cited = {{9}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{0}},
Journal-ISO = {{npj Clim. Atmos. Sci.}},
Doc-Delivery-Number = {{HY3FC}},
Unique-ID = {{ISI:000468007700048}},
OA = {{DOAJ Gold, Green Published}},
DA = {{2020-08-06}},
}

@article{ ISI:000468007700021,
Author = {Allen, Robert J. and Anderson, Ray G.},
Title = {{21st century California drought risk linked to model fidelity of the El
   Nino teleconnection}},
Journal = {{NPJ CLIMATE AND ATMOSPHERIC SCIENCE}},
Year = {{2018}},
Volume = {{1}},
Abstract = {{Greenhouse gas induced climate change is expected to lead to negative
   hydrological impacts for southwestern North America, including
   California (CA). This includes a decrease in the amount and frequency of
   precipitation, reductions in Sierra snow pack, and an increase in
   evapotranspiration, all of which imply a decline in surface water
   availability, and an increase in drought and stress on water resources.
   However, a recent study showed the importance of tropical Pacific sea
   surface temperature (SST) warming and an El Nino Southern Oscillation
   (ENSO)-like teleconnection in driving an increase in CA precipitation
   through the 21st century, particularly during winter (DJF). Here, we
   extend this prior work and show wetter (drier) CA conditions, based on
   several drought metrics, are associated with an El Nino (La Nina)-like
   SST pattern. Models that better simulate the observed ENSO-CA
   precipitation teleconnection also better simulate the ENSO-CA drought
   relationships, and yield negligible change in the risk of 21st century
   CA drought, primarily due to wetting during winter. Seasonally, however,
   CA drought risk is projected to increase during the non-winter months,
   particularly in the models that poorly simulate the observed
   teleconnection. Thus, future projections of CA drought are dependent on
   model fidelity of the El Nino teleconnection. As opposed to focusing on
   adapting to less water, models that better simulate the teleconnection
   imply adaptation measures focused on smoothing seasonal differences for
   affected agricultural, terrestrial, and aquatic systems, as well as
   effectively capturing enhanced winter runoff.}},
Publisher = {{NATURE PUBLISHING GROUP}},
Address = {{MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Allen, RJ (Corresponding Author), Univ Calif Riverside, Dept Earth Sci, Riverside, CA 92521 USA.
   Allen, Robert J., Univ Calif Riverside, Dept Earth Sci, Riverside, CA 92521 USA.
   Anderson, Ray G., ARS, Salin Lab, USDA, George E Brown Jr Salin Lab, 450 W Big Springs Rd, Riverside, CA 92507 USA.}},
DOI = {{10.1038/s41612-018-0032-x}},
Article-Number = {{21}},
ISSN = {{2397-3722}},
Keywords-Plus = {{CLIMATE-CHANGE; SOIL-MOISTURE; WINTER PRECIPITATION; PATTERNS; NORTHERN;
   RAINFALL; PACIFIC; INDEX; CMIP5; ENSO}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{rjallen@ucr.edu}},
ORCID-Numbers = {{Anderson, Ray/0000-0002-6202-5890}},
Funding-Acknowledgement = {{NSFNational Science Foundation (NSF) {[}AGS-1455682]}},
Funding-Text = {{This study was funded by NSF award AGS-1455682.}},
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