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Number-of-Cited-References = {{61}},
Times-Cited = {{28}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{18}},
Journal-ISO = {{J. Hydrometeorol.}},
Doc-Delivery-Number = {{FZ1TI}},
Unique-ID = {{ISI:000427359900009}},
OA = {{Bronze}},
DA = {{2020-08-06}},
}

@article{ ISI:000417079400080,
Author = {Wang, Zhaohua and Yang, Yuantao and Wang, Bo},
Title = {{Carbon footprints and embodied CO2 transfers among provinces in China}},
Journal = {{RENEWABLE \& SUSTAINABLE ENERGY REVIEWS}},
Year = {{2018}},
Volume = {{82}},
Number = {{1}},
Pages = {{1068-1078}},
Month = {{FEB}},
Abstract = {{China is the top CO2 emitter with enormous regional variation in
   economic development, resource endowment, and consumption patterns,
   which leads to great variations in regional CO2 emissions and embodied
   CO2 transfer among provinces. Analyzing the mechanisms responsible for
   carbon footprint (CF) and embodied CO2 transfer among provinces via
   trade could help policy makers allocate emission responsibilities and
   reduction targets. Based on a multi-regional input-output model, this
   paper investigates the CFs and embodied CO2 transfer in/among 30
   provinces of China in 2007 and 2010, and analyzes emissions from
   different perspectives. Results indicate that China's CF grew from 5230
   Mt in 2007 to 6922 Mt in 2010, with an annual growth rate of 9.8\%. The
   provinces with the large CFs and per capita CF were mainly those locate
   in eastern, developed regions along the coast and several highly
   populated ones. CO2 emissions due to capital formation contributes the
   most to the CFs and the increment in this period, and this was followed
   by urban consumption. Significant embodied CO2 transfer were observed to
   drift from the developing and energy-abundant provinces like Hebei and
   Inner Mongolia, to the developed coastal provinces. Total embodied CO2
   transfer account for 43.9\% of the national CF in 2007, and decreased to
   41.0\% in 2010. In order to control CO2 emissions and make reduction
   allocations for provinces, interprovincial embodied CO2 transfer and
   practical capacities need to be taken into account.}},
Publisher = {{PERGAMON-ELSEVIER SCIENCE LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}},
Type = {{Review}},
Language = {{English}},
Affiliation = {{Wang, ZH (Corresponding Author), Beijing Inst Technol, Sch Management \& Econ, Beijing 100081, Peoples R China.
   Wang, Zhaohua; Yang, Yuantao; Wang, Bo, Beijing Inst Technol, Sch Management \& Econ, Beijing 100081, Peoples R China.
   Wang, Zhaohua; Yang, Yuantao, Beijing Inst Technol, Ctr Energy \& Environm Policy Res, Beijing 100081, Peoples R China.
   Wang, Zhaohua, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China.
   Wang, Zhaohua, Beijing Key Lab Energy Econ \& Environm Management, Beijing 100081, Peoples R China.
   Wang, Zhaohua, Sustainable Dev Res Inst Econ \& Soc Beijing, Beijing 100081, Peoples R China.}},
DOI = {{10.1016/j.rser.2017.09.057}},
ISSN = {{1364-0321}},
EISSN = {{1879-0690}},
Keywords = {{Carbon footprint; Multi-regional input-output; Embodied CO2 transfer;
   Provincial level; Regional variation}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; INTERNATIONAL-TRADE; DIOXIDE EMISSIONS;
   CONSUMPTION; INVENTORIES; ENERGY; UK}},
Research-Areas = {{Science \& Technology - Other Topics; Energy \& Fuels}},
Web-of-Science-Categories  = {{Green \& Sustainable Science \& Technology; Energy \& Fuels}},
Author-Email = {{wangzhaohua@bit.edu.cn}},
ORCID-Numbers = {{Yang, Yuantao/0000-0001-6344-9727}},
Funding-Acknowledgement = {{National Key Research and Development Program of China
   {[}2016YFA0602504, 2016YFA0602502]; National Science Fund for
   Distinguished Young ScholarsNational Natural Science Foundation of
   ChinaNational Science Fund for Distinguished Young Scholars
   {[}71625003]; National Natural Science Foundation of ChinaNational
   Natural Science Foundation of China {[}71573016, 71521002, 71403021,
   71774014]; Humanities and Social science Fund of Ministry of Education
   of ChinaMinistry of Education, China {[}17YJC630145]}},
Funding-Text = {{This study is supported by the National Key Research and Development
   Program of China (Reference nos. 2016YFA0602504, 2016YFA0602502),
   National Science Fund for Distinguished Young Scholars (Reference no.
   71625003), National Natural Science Foundation of China (Reference nos.
   71573016, 71521002, 71403021, 71774014)., and Humanities and Social
   science Fund of Ministry of Education of China (Reference No.
   17YJC630145). The authors are grateful for the data support from Key
   Laboratory of Regional Sustainable Development Modeling, Chinese Academy
   of Sciences and want to thank Professor Yiming Wei and Dr. Bin Zhang for
   their constructive comments and suggestions.}},
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Number-of-Cited-References = {{51}},
Times-Cited = {{34}},
Usage-Count-Last-180-days = {{8}},
Usage-Count-Since-2013 = {{104}},
Journal-ISO = {{Renew. Sust. Energ. Rev.}},
Doc-Delivery-Number = {{FO7TJ}},
Unique-ID = {{ISI:000417079400080}},
DA = {{2020-08-06}},
}

@article{ ISI:000419417300031,
Author = {Tang, Xu and Jin, Yi and McLellan, Benjamin C. and Wang, Jianliang and
   Li, Shiqun},
Title = {{China's coal consumption declining-Impermanent or permanent?}},
Journal = {{RESOURCES CONSERVATION AND RECYCLING}},
Year = {{2018}},
Volume = {{129}},
Pages = {{307-313}},
Month = {{FEB}},
Abstract = {{Coal dominates China's energy consumption, and academic published papers
   especially before 2010 usually undervalued China's coal consumption
   significantly. However, China's coal consumption has declined
   continuously in 2014 and 2015. This seems to indicate that China may
   have finally reached the peak of its coal consumption in 2013. There is
   minimal quantitative research on the analysis of this phenomenon. The
   logarithmic mean Divisia index (LMDI) method is used in this study to
   analyze the key factors that drive China's direct coal consumption
   variation. Approaching the issue from the perspective of indirect coal
   consumption, an Input-Output model is established to discuss China's
   embodied coal exports in this study, aiming to trace the ultimate demand
   for coal to understand why consumption might have peaked. The research
   results suggest that changes of industrial structure started to reduce
   China's coal consumption significantly since 2012, and the effects of
   energy intensity and energy mix have continued to play important roles
   in coal consumption reduction since 2007, especially the energy mix
   effect since 2012. On the other side of the equation, although the
   economic scale effect - the only factor apparently driving increases in
   China's coal consumption - is still large, the increasing trend has
   reversed, and its impact has stabilised. China's embodied coal exports,
   both absolute volume and the proportion of coal consumption, are falling
   even though the trade surplus has still been increasing in recent years,
   which is completely different with the trend before 2011. China's
   continuous efforts on export restructuring - shifting from labour \&
   energy-intensive to capital \& technology-intensive - will reduce
   embodied coal exports and coal consumption in the future. (C) 2016
   Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Tang, X (Corresponding Author), China Univ Petr, Sch Business Adm, Beijing 102249, Peoples R China.
   Tang, Xu; Jin, Yi; Wang, Jianliang; Li, Shiqun, China Univ Petr, Sch Business Adm, Beijing 102249, Peoples R China.
   McLellan, Benjamin C., Kyoto Univ, Grad Sch Energy Sci, Sakyo Ku, Kyoto 6068501, Japan.}},
DOI = {{10.1016/j.resconrec.2016.07.018}},
ISSN = {{0921-3449}},
EISSN = {{1879-0658}},
Keywords = {{Coal consumption; Embodied energy; Energy structure; LMDI; Input-output
   analysis}},
Keywords-Plus = {{INTERNATIONAL-TRADE; ENERGY-CONSUMPTION; DECOMPOSITION; INTENSITY;
   CHALLENGES; EMISSIONS; OIL}},
Research-Areas = {{Engineering; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Engineering, Environmental; Environmental Sciences}},
Author-Email = {{tangxu2001@163.com}},
ResearcherID-Numbers = {{McLellan, Benjamin C/B-7833-2009
   Wang, Jianliang/D-9149-2019
   }},
ORCID-Numbers = {{McLellan, Benjamin C/0000-0002-4802-3864
   Wang, Jianliang/0000-0001-7037-9368
   Tang, Xu/0000-0003-3068-1524}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71303258, 71373285, 71503264]; National Social
   Science Funds of China {[}13ZD159]; Research Fund for the Doctoral
   Program of Higher Education of ChinaResearch Fund for the Doctoral
   Program of Higher Education of China (RFDP)Specialized Research Fund for
   the Doctoral Program of Higher Education (SRFDP) {[}20120007120015]; MOE
   (Ministry of Education in China) Project of Humanities and Social
   Sciences {[}13YJC630148, 15YJC630121]; Science Foundation of China
   University of Petroleum, Beijing {[}ZX20150130]}},
Funding-Text = {{The authors appreciate the National Natural Science Foundation of
   China(71303258, 71373285, 71503264), National Social Science Funds of
   China (13\&ZD159), Research Fund for the Doctoral Program of Higher
   Education of China (20120007120015), MOE (Ministry of Education in
   China) Project of Humanities and Social Sciences (13YJC630148,
   15YJC630121), and Science Foundation of China University of Petroleum,
   Beijing (ZX20150130) for sponsoring this research.}},
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Number-of-Cited-References = {{34}},
Times-Cited = {{39}},
Usage-Count-Last-180-days = {{5}},
Usage-Count-Since-2013 = {{61}},
Journal-ISO = {{Resour. Conserv. Recycl.}},
Doc-Delivery-Number = {{FR9TZ}},
Unique-ID = {{ISI:000419417300031}},
DA = {{2020-08-06}},
}

@article{ ISI:000414160500096,
Author = {Chen, B. and Hanb, M. Y. and Peng, K. and Zhou, S. L. and Shao, L. and
   Wu, X. F. and Wei, W. D. and Liu, S. Y. and Li, Z. and Li, J. S. and
   Chen, G. Q.},
Title = {{Global land-water nexus: Agricultural land and freshwater use embodied
   in worldwide supply chains}},
Journal = {{SCIENCE OF THE TOTAL ENVIRONMENT}},
Year = {{2018}},
Volume = {{613}},
Pages = {{931-943}},
Month = {{FEB 1}},
Abstract = {{As agricultural land and freshwater inextricably interrelate and
   interact with each other, the conventional water and land policy in
   ``silos{''} should give way to nexus thinking when formulating the land
   and water management strategies. This study constructs a systems
   multi-regional input-output (MRIO) model to expound global land-water
   nexus by simultaneously tracking agricultural land and freshwater use
   flows along the global supply chains. Furthermore, land productivity and
   irrigationwater requirements of 160 crops in different regions are
   investigated to reflect the land-water linkage. Results show that
   developed economies (e.g., USA and Japan) and major large developing
   economies (e.g., mainland China and India) are the overriding drivers of
   agricultural land and freshwater use globally. In general, significant
   net transfers of these two resources are identified from resource-rich
   and less-developed economies to resource-poor and more-developed
   economies. For some crops, bluewater productivity is inversely related
   to land productivity, indicating that irrigationwater consumption is
   sometimes at odds with land use. The results could stimulus
   international cooperation for sustainable land and freshwater management
   targeting on original suppliers and final consumers along the global
   supply chains. Moreover, crop-specific land-water linkage could provide
   insights for trade-off decisions on minimizing the environmental impacts
   on local land and water resources. (C) 2017 Elsevier B.V. All rights
   reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Chen, GQ (Corresponding Author), Peking Univ, Coll Engn, Lab Syst Ecol \& Sustainabil Sci, Beijing 100871, Peoples R China.
   Li, JS (Corresponding Author), Huazhong Univ Sci \& Technol, Sch Energy \& Power Engn, Dept New Energy Sci \& Engn, Wuhan 430074, Hubei, Peoples R China.
   Chen, B.; Li, Z.; Chen, G. Q., Peking Univ, Coll Engn, Lab Syst Ecol \& Sustainabil Sci, Beijing 100871, Peoples R China.
   Hanb, M. Y., Chinese Acad Sci, Inst Geog Sci \& Nat Resources Res, Beijing 100101, Peoples R China.
   Peng, K.; Li, J. S., Huazhong Univ Sci \& Technol, Sch Energy \& Power Engn, Dept New Energy Sci \& Engn, Wuhan 430074, Hubei, Peoples R China.
   Zhou, S. L.; Li, J. S., Huazhong Univ Sci \& Technol, State Key Lab Coal Combust, Wuhan 430074, Hubei, Peoples R China.
   Shao, L., China Univ Geosci, Sch Humanities \& Econ Management, Beijing 100083, Peoples R China.
   Wu, X. F., Zhongnan Univ Econ \& Law, Econ Sch, Wuhan 430073, Hubei, Peoples R China.
   Wei, W. D., Univ Shanghai Sci \& Technol, Business Sch, Shanghai 200093, Peoples R China.
   Liu, S. Y., Yanshan Univ, Hebei Prov Key Lab Heavy Machinery Fluid Power Tr, Qinhuangdao 066004, Peoples R China.}},
DOI = {{10.1016/j.scitotenv.2017.09.138}},
ISSN = {{0048-9697}},
EISSN = {{1879-1026}},
Keywords = {{Land use; Blue water consumption; Agriculture; Nexus; Global supply
   chains}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; INTERNATIONAL-TRADE; ENVIRONMENTAL IMPACTS;
   ENERGY-CONSUMPTION; MERCURY EMISSIONS; CARBON FOOTPRINT; CLIMATE-CHANGE;
   FOOD NEXUS; DEFICIT IRRIGATION; CO2 EMISSIONS}},
Research-Areas = {{Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Environmental Sciences}},
Author-Email = {{lijiashuo@hust.edu.cn
   gqchen@pku.edu.cn}},
ResearcherID-Numbers = {{（陈国谦）, Guoqian Chen/B-5407-2012
   shao, ling/A-9483-2011
   Wu, Xiaofang/O-7253-2014
   Peng, Kun/H-1487-2019
   Chen, Bin/E-1760-2017
   Li, Jiashuo/K-5809-2013}},
ORCID-Numbers = {{（陈国谦）, Guoqian Chen/0000-0003-1173-6796
   Chen, Bin/0000-0001-8326-4551
   Li, Jiashuo/0000-0002-2915-4770}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71704060, 41701135]; Natural Science Foundation
   of Hubei ProvinceNatural Science Foundation of Hubei Province
   {[}2016CFB132]; National Key Research and Development Program of China
   {[}2016YFA0602800]; Fundamental Research Funds for the Central
   Universities, HUSTFundamental Research Funds for the Central
   Universities {[}2016YXMS043, 2016YXZD007]}},
Funding-Text = {{The research is supported by the National Natural Science Foundation of
   China (No. 71704060 and 41701135), the Natural Science Foundation of
   Hubei Province (No. 2016CFB132), the National Key Research and
   Development Program of China (No. 2016YFA0602800) and the Fundamental
   Research Funds for the Central Universities, HUST (No. 2016YXMS043 and
   No. 2016YXZD007).}},
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Number-of-Cited-References = {{97}},
Times-Cited = {{86}},
Usage-Count-Last-180-days = {{32}},
Usage-Count-Since-2013 = {{393}},
Journal-ISO = {{Sci. Total Environ.}},
Doc-Delivery-Number = {{FL3XT}},
Unique-ID = {{ISI:000414160500096}},
ESI-Highly-Cited-Paper = {{Y}},
ESI-Hot-Paper = {{N}},
DA = {{2020-08-06}},
}

@article{ ISI:000430909700016,
Author = {Li, Hui and Zhai, Panmao and Chen, Yang and Lu, Er},
Title = {{Potential Influence of the East Asia-Pacific Teleconnection Pattern on
   Persistent Precipitation in South China: Implications of Atypical
   Yangtze River Valley Cases}},
Journal = {{WEATHER AND FORECASTING}},
Year = {{2018}},
Volume = {{33}},
Number = {{1}},
Pages = {{267-282}},
Month = {{FEB}},
Abstract = {{In this study, cases of the East Asia-Pacific (EAP) teleconnection
   pattern not responsible for persistent precipitation processes in the
   Yangtze River valley (YRV) have been investigated. The results suggest
   that such a type of EAP pattern has some linkage with persistent
   precipitation processes in south China (SC) with the following
   properties: 1) in response to the negative SSTAs and anticyclone near
   the Philippines, the meridional energy propagates from the low latitudes
   over the north of the Philippines; 2) the western Pacific subtropical
   high (WPSH) then intensifies and extends westward; 3) a meridional
   triple structure of the EAP teleconnection pattern is established; 4) at
   the same time, the cyclonic circulation over northeastern China
   introduces cold and dry air to the lower latitudes, merging with the
   water vapor into SC and leading to heavy precipitation from the fringe
   of the WPSH, the South China Sea, and the Bay of Bengal and the
   combination of systems persists for at least 3 days, leading to the
   persistent precipitation processes in SC; and 5) compared with the EAP
   teleconnection responsible for the precipitation in YRV, the positions
   of the three centers in the mid- and low latitudes are more southerly
   located than the YRV EAP centers. Further study indicates that the ocean
   surface heat conditions in the areas near the Philippines seem to be
   important in affecting the EAP teleconnection pattern for persistent
   precipitation processes in SC. Finally, all of the cases with persistent
   precipitation in SC during 1961-2010 linked with the EAP pattern have
   been investigated; the results are consistent with the above
   conclusions.}},
Publisher = {{AMER METEOROLOGICAL SOC}},
Address = {{45 BEACON ST, BOSTON, MA 02108-3693 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Zhai, PM (Corresponding Author), China Acad Meteorol Sci, State Key Lab Severe Weather, Beijing, Peoples R China.
   Li, Hui; Zhai, Panmao; Chen, Yang, China Acad Meteorol Sci, State Key Lab Severe Weather, Beijing, Peoples R China.
   Li, Hui; Lu, Er, Nanjing Univ Informat Sci \& Technol, Joint Int Res Lab Climate \& Environm Change ILCEC, Collaborat Innovat Ctr Forecast \& Evaluat Meteoro, Key Lab Meteorol Disaster,Minist Educ KLME, Nanjing, Jiangsu, Peoples R China.}},
DOI = {{10.1175/WAF-D-17-0011.1}},
ISSN = {{0882-8156}},
EISSN = {{1520-0434}},
Keywords-Plus = {{SEASON PRECIPITATION; SUMMER; EVENTS; ANOMALIES; WAVES; TEMPERATURE;
   VARIABILITY; CIRCULATION; MECHANISMS; FLOW}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{pmzhai@cma.gov.cn}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}41605029, 41575094, 41565005]; China Special Fund
   for Meteorological Research in the Public Interest {[}GYHY201506001]}},
Funding-Text = {{This study was jointly supported by the National Natural Science
   Foundation of China (41605029, 41575094 and 41565005) and the China
   Special Fund for Meteorological Research in the Public Interest
   (GYHY201506001). The authors declare no competing financial interests
   regarding the publication of this paper.}},
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Number-of-Cited-References = {{34}},
Times-Cited = {{4}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{13}},
Journal-ISO = {{Weather Forecast.}},
Doc-Delivery-Number = {{GE0MZ}},
Unique-ID = {{ISI:000430909700016}},
OA = {{Bronze}},
DA = {{2020-08-06}},
}

@article{ ISI:000428474500015,
Author = {Lee, Donghoon and Ward, Philip and Block, Paul},
Title = {{Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and
   Prospects for Prediction Globally}},
Journal = {{WATER RESOURCES RESEARCH}},
Year = {{2018}},
Volume = {{54}},
Number = {{2}},
Pages = {{916-938}},
Month = {{FEB}},
Abstract = {{Flood-related fatalities and impacts on society surpass those from all
   other natural disasters globally. While the inclusion of large-scale
   climate drivers in streamflow (or high-flow) prediction has been widely
   studied, an explicit link to global-scale long-lead prediction is
   lacking, which can lead to an improved understanding of potential flood
   propensity. Here we attribute seasonal peak-flow to large-scale climate
   patterns, including the El Nino Southern Oscillation (ENSO), Pacific
   Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and
   Atlantic Multidecadal Oscillation (AMO), using streamflow station
   observations and simulations from PCR-GLOBWB, a global-scale hydrologic
   model. Statistically significantly correlated climate patterns and
   streamflow autocorrelation are subsequently applied as predictors to
   build a global-scale season-ahead prediction model, with prediction
   performance evaluated by the mean squared error skill score (MSESS) and
   the categorical Gerrity skill score (GSS). Globally, fair-to-good
   prediction skill (20\% <= MSESS and 0.2 <= GSS) is evident for a number
   of locations (28\% of stations and 29\% of land area), most notably in
   data-poor regions (e.g., West and Central Africa). The persistence of
   such relevant climate patterns can improve understanding of the
   propensity for floods at the seasonal scale. The prediction approach
   developed here lays the groundwork for further improving local-scale
   seasonal peak-flow prediction by identifying relevant global-scale
   climate patterns. This is especially attractive for regions with limited
   observations and or little capacity to develop flood early warning
   systems.}},
Publisher = {{AMER GEOPHYSICAL UNION}},
Address = {{2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Block, P (Corresponding Author), Univ Wisconsin Madison, Dept Civil \& Environm Engn, Madison, WI 53706 USA.
   Lee, Donghoon; Block, Paul, Univ Wisconsin Madison, Dept Civil \& Environm Engn, Madison, WI 53706 USA.
   Ward, Philip, Vrije Univ Amsterdam, Inst Environm Studies, Dept Water \& Climate Risk, Amsterdam, Netherlands.}},
DOI = {{10.1002/2017WR021205}},
ISSN = {{0043-1397}},
EISSN = {{1944-7973}},
Keywords-Plus = {{NORTH-ATLANTIC OSCILLATION; NINO-SOUTHERN-OSCILLATION; LONG-RANGE
   STREAMFLOW; PRECIPITATION; VARIABILITY; ENSO; FORECASTS; PACIFIC;
   PREDICTABILITY; TELECONNECTION}},
Research-Areas = {{Environmental Sciences \& Ecology; Marine \& Freshwater Biology; Water
   Resources}},
Web-of-Science-Categories  = {{Environmental Sciences; Limnology; Water Resources}},
Author-Email = {{paul.block@wisc.edu}},
ResearcherID-Numbers = {{Ward, Philip/E-6208-2010
   Lee, Donghoon/O-3196-2015
   }},
ORCID-Numbers = {{Lee, Donghoon/0000-0001-5438-903X
   Block, Paul/0000-0003-1993-7496}},
Funding-Acknowledgement = {{Global Health Institute; Graduate School of the University of
   Wisconsin-Madison; Netherlands Organisation for Scientific Research
   (NWO)Netherlands Organization for Scientific Research (NWO)
   {[}016.161.324]}},
Funding-Text = {{We thank the GRDC for providing streamflow observations. The GRDC
   streamflow data are freely available on request
   (http://www.bafg.de/GRDC/EN/Home/homepage\_node.html). The PCR-GLOBWB
   simulation data used in this study and Ward et al. (2013) are originally
   obtained from Utrecht University and available on request
   (http://www.earthsurfacehydrology.nl/). Funding for D.L. was provided by
   Global Health Institute and the Graduate School of the University of
   Wisconsin-Madison. P.J.W. received funding from the Netherlands
   Organisation for Scientific Research (NWO) in the form of a VIDI grant
   (grant 016.161.324). We also thank the editor and three anonymous
   reviewers for their valuable comments and suggestions.}},
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Number-of-Cited-References = {{87}},
Times-Cited = {{9}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{Water Resour. Res.}},
Doc-Delivery-Number = {{GA6WD}},
Unique-ID = {{ISI:000428474500015}},
DA = {{2020-08-06}},
}

@article{ ISI:000427507000032,
Author = {Ptak, Mariusz and Tomczyk, Arkadiusz M. and Wrzesinski, Dariusz},
Title = {{Effect of Teleconnection Patterns on Changes in Water Temperature in
   Polish Lakes}},
Journal = {{ATMOSPHERE}},
Year = {{2018}},
Volume = {{9}},
Number = {{2}},
Month = {{FEB}},
Abstract = {{The objective of the paper was the determination of the effect of
   teleconnection patterns (North Atlantic Oscillation (NAO), Arctic
   Oscillation (AO), East Atlantic pattern (EA), East Atlantic/Western
   Russia (EAWR), and Scandinavian pattern (SCAND)) on changes in air and
   water temperature in Polish lakes. Correlations of circulation indices
   with air and lake water temperature were analysed in the monthly cycle.
   Deviations of values of such components in different phases of the
   analysed atmospheric circulations types from mean average from the years
   1971 to 2015 were also determined. The research showed a variable effect
   of the atmospheric circulations types. The strongest effect on water
   temperature was observed in winter, when AO and NAO circulation showed
   particularly evident influence. Deviations of water temperature from
   mean values from the analysed multi-annual period generally oscillated
   around 1.0 degrees C, reaching a maximum value of 1.4 degrees C. The
   presented research shows the complexity of processes determining changes
   in lake water temperature, the course of which depends on many factors
   with both regional (e.g., ice cover on lakes) and local range
   (conditions of water exchange, human pressure).}},
Publisher = {{MDPI}},
Address = {{ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Ptak, M (Corresponding Author), Adam Mickiewicz Univ, Inst Phys Geog \& Environm Planning, B Krygowskiego 10, PL-61680 Poznan, Poland.
   Ptak, Mariusz; Tomczyk, Arkadiusz M.; Wrzesinski, Dariusz, Adam Mickiewicz Univ, Inst Phys Geog \& Environm Planning, B Krygowskiego 10, PL-61680 Poznan, Poland.}},
DOI = {{10.3390/atmos9020066}},
Article-Number = {{66}},
ISSN = {{2073-4433}},
Keywords = {{teleconnection patterns; air temperature; water temperature; lakes;
   Central Europe}},
Keywords-Plus = {{NORTH-ATLANTIC OSCILLATION; CIRCULATION PATTERNS; ICE COVER; GERMAN
   LOWLANDS; AIR-TEMPERATURE; CENTRAL-EUROPE; LONG-TERM; CLIMATE;
   VARIABILITY; STREAMFLOW}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{marp114@wp.pl
   atomczyk@amu.edu.pl
   darwrze@amu.edu.pl}},
ResearcherID-Numbers = {{Ptak, Mariusz/O-3217-2015
   Wrzesinski, Dariusz/I-5765-2019
   }},
ORCID-Numbers = {{Ptak, Mariusz/0000-0003-1225-1686
   Wrzesinski, Dariusz/0000-0001-5025-1447
   Tomczyk, Arkadiusz Marek/0000-0003-1576-8795}},
Funding-Acknowledgement = {{Polish National Science Centre {[}UMO-2014/15/N/ST10/00717]}},
Funding-Text = {{This work was partly supported by the Polish National Science Centre
   under grant number UMO-2014/15/N/ST10/00717.}},
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Number-of-Cited-References = {{55}},
Times-Cited = {{13}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Atmosphere}},
Doc-Delivery-Number = {{FZ3RF}},
Unique-ID = {{ISI:000427507000032}},
OA = {{DOAJ Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000427664100011,
Author = {Paiva de Medeiros, Renan Landau and Barra, Jr., Walter and de Bessa,
   Iury Valente and Chaves Filho, Joao Edgar and de Cavalho Ayres, Jr.,
   Florindo Antonio and das Neves, Cleonor Crescencio},
Title = {{Robust decentralized controller for minimizing coupling effect in single
   inductor multiple output DC-DC converter operating in continuous
   conduction mode}},
Journal = {{ISA TRANSACTIONS}},
Year = {{2018}},
Volume = {{73}},
Pages = {{112-129}},
Month = {{FEB}},
Abstract = {{This paper describes a novel robust decentralized control design
   methodology for a single inductor multiple output (SIMO) DC-DC
   converter. Based on a nominal multiple input multiple output (MIMO)
   plant model and performance requirements, a pairing input-output
   analysis is performed to select the suitable input to control each
   output aiming to attenuate the loop coupling. Thus, the plant
   uncertainty limits are selected and expressed in interval form with
   parameter values of the plant model. A single inductor dual output
   (SIDO) DC-DC buck converter board is developed for experimental tests.
   The experimental results show that the proposed methodology can maintain
   a desirable performance even in the presence of parametric
   uncertainties. Furthermore, the performance indexes calculated from
   experimental data show that the proposed methodology outperforms
   classical MIMO control techniques. (C) 2018 ISA. Published by Elsevier
   Ltd. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE INC}},
Address = {{360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{de Medeiros, RLP (Corresponding Author), Fed Univ Amazonas UFAM, Dept Elect, Av Rodrigo Octavio 6200, BR-69080900 Coroado 1, Brazil.
   Paiva de Medeiros, Renan Landau; de Bessa, Iury Valente; Chaves Filho, Joao Edgar; de Cavalho Ayres, Florindo Antonio, Jr., Fed Univ Amazonas UFAM, Dept Elect, Av Rodrigo Octavio 6200, BR-69080900 Coroado 1, Brazil.
   Barra, Walter, Jr., Fed Univ Para UFPa, Fac Elect Engn, Campus Guama, BR-66075900 Belem, Para, Brazil.
   das Neves, Cleonor Crescencio, Fed Inst Educ Sci \& Technol Amazonas IFAM, Av 7 Setembro,1975 Ctr, BR-69020120 Manaus, Amazonas, Brazil.}},
DOI = {{10.1016/j.isatra.2018.01.006}},
ISSN = {{0019-0578}},
EISSN = {{1879-2022}},
Keywords = {{Single inductor multiple output DC-DC converter; Robust decentralized
   controller; Parametric uncertainties; Pairing analysis; Effective
   relative gain array; Integral square error performance index}},
Keywords-Plus = {{DESIGN}},
Research-Areas = {{Automation \& Control Systems; Engineering; Instruments \&
   Instrumentation}},
Web-of-Science-Categories  = {{Automation \& Control Systems; Engineering, Multidisciplinary;
   Instruments \& Instrumentation}},
Author-Email = {{renanlandau@yahoo.com.br
   walbarra@ufpa.br
   iury.bessa@gmail.com
   joaoedgarc@gmail.com
   florindoayres@yahoo.com
   cleonor@ifam.edu.br}},
ResearcherID-Numbers = {{Bessa, Iury/V-6714-2017
   de Carvalho Ayres Junior, Florindo Antonio/AAO-7973-2020
   de Medeiros, Renan Landau Paiva/R-5199-2019
   }},
ORCID-Numbers = {{Bessa, Iury/0000-0002-6603-3476
   de Medeiros, Renan Landau Paiva/0000-0002-1645-2736
   Ayres Junior, Florindo Antonio de Carvalho/0000-0002-0266-1019}},
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Number-of-Cited-References = {{39}},
Times-Cited = {{4}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{6}},
Journal-ISO = {{ISA Trans.}},
Doc-Delivery-Number = {{FZ5VJ}},
Unique-ID = {{ISI:000427664100011}},
DA = {{2020-08-06}},
}

@article{ ISI:000424900100006,
Author = {Xiao, Yanyan and Lenzen, Manfred and Benoit-Norris, Catherine and
   Norris, Gregory A. and Murray, Joy and Malik, Arunima},
Title = {{The Corruption Footprints of Nations}},
Journal = {{JOURNAL OF INDUSTRIAL ECOLOGY}},
Year = {{2018}},
Volume = {{22}},
Number = {{1}},
Pages = {{68-78}},
Month = {{FEB}},
Abstract = {{In this study, we innovatively apply multiregional input-output analysis
   to calculate corruption footprints of nations and show the details of
   commodities that use the most employment affected by corruption (EAC),
   as they flow between countries. Every country's corruption footprint
   includes its domestic corruption and the corruption imported by global
   supply chains to meet final demand. Our results show that, generally,
   the net corruption exporters are developing countries, with the
   exception of Italy where corruption is likely to be more affected by
   political and cultural factors than economic factors. China is the
   largest gross corruption exporter, and India follows close behind, with
   clothing as one of the industries in which the most people are affected
   by corruption. This is because: (1) China and India are major clothing
   exporters, thus many workers are employed in the clothing industry
   within the country as well as in countries providing intermediate
   commodities by supply chains, and (2) corruption is high in China and
   India. Our results can be useful to identify where regulations to combat
   corruption can have the greatest impact. More important, the method we
   use can be applied to link corruption to other economic and social
   aspects of trade, such as working conditions, thus making it possible to
   find avenues for tackling the problem that are not usually considered in
   anticorruption strategies.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lenzen, M (Corresponding Author), Univ Sydney, ISA, Sch Phys A28,501, Sydney, NSW 2006, Australia.
   Xiao, Yanyan; Murray, Joy; Malik, Arunima, Univ Sydney, Ctr Integrated Sustainabil Anal, Sydney, NSW, Australia.
   Lenzen, Manfred, Univ Sydney, Ctr Integrated Sustainabil Anal, Sustainabil Res, Sydney, NSW, Australia.
   Benoit-Norris, Catherine, Harvard Sch Publ Hlth, Social Sustainabil, Social Hotspots Database Project, New Earth, Boston, MA USA.
   Norris, Gregory A., Harvard Sch Publ Hlth, New Earth, Boston, MA USA.}},
DOI = {{10.1111/jiec.12537}},
ISSN = {{1088-1980}},
EISSN = {{1530-9290}},
Keywords = {{corruption footprint; industrial ecology; input-output analysis (IOA);
   international trade; multiregional input-output tables; social science}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; INTERNATIONAL-TRADE; DATABASE; IMPACTS; ECONOMY;
   CHAINS; WATER}},
Research-Areas = {{Science \& Technology - Other Topics; Engineering; Environmental
   Sciences \& Ecology}},
Web-of-Science-Categories  = {{Green \& Sustainable Science \& Technology; Engineering, Environmental;
   Environmental Sciences}},
Author-Email = {{manfred.lenzen@sydney.edu.au}},
ResearcherID-Numbers = {{Silva, Francisco Javier Gonzalez/AAQ-5083-2020
   }},
ORCID-Numbers = {{Silva, Francisco Javier Gonzalez/0000-0002-6618-2922
   Lenzen, Manfred/0000-0002-0828-5288
   Malik, Arunima/0000-0002-4630-9869}},
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