text:
CLEAN PROD, V178, P276, DOI 10.1016/j.jclepro.2017.12.175.
   Weinzettel J, 2013, GLOBAL ENVIRON CHANG, V23, P433, DOI 10.1016/j.gloenvcha.2012.12.010.
   Wiedmann T, 2006, ECOL ECON, V56, P28, DOI 10.1016/j.ecolecon.2005.05.012.
   Wilting HC, 2009, ECON SYST RES, V21, P291, DOI 10.1080/09535310903541736.
   WorldBank, 2017, WORLD BANK OP DAT.
   Wu XD, 2018, ENERG POLICY, V117, P358, DOI 10.1016/j.enpol.2018.02.043.
   Wu XD, 2017, APPL ENERG, V195, P125, DOI 10.1016/j.apenergy.2017.03.029.
   Wu XD, 2016, APPL ENERG, V184, P936, DOI 10.1016/j.apenergy.2016.03.027.
   Wu XF, 2018, RENEW SUST ENERG REV, V81, P978, DOI 10.1016/j.rser.2017.08.018.
   Wu XF, 2017, ENERG POLICY, V108, P81, DOI 10.1016/j.enpol.2017.05.048.
   Wurtenberger L, 2006, ECOL ECON, V57, P679, DOI 10.1016/j.ecolecon.2005.06.004.
   Yu Y, 2013, GLOBAL ENVIRON CHANG, V23, P1178, DOI 10.1016/j.gloenvcha.2013.04.006.
   Zhang B, 2010, ENERG POLICY, V38, P4304, DOI 10.1016/j.enpol.2010.03.059.}},
Number-of-Cited-References = {{80}},
Times-Cited = {{21}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{25}},
Journal-ISO = {{Land Use Pol.}},
Doc-Delivery-Number = {{GJ8DQ}},
Unique-ID = {{ISI:000435619900021}},
OA = {{Bronze}},
DA = {{2020-08-06}},
}

@article{ ISI:000433266000026,
Author = {Ma, Fengmei and Wang, Heming and Zhu, Bing and Chen, Dingjiang and Dai,
   Hancheng and Wang, Jian and Zhao, Shen and Yue, Qiang and Zhang,
   Guangsheng and Xie, Yang and Geng, Yong and Du, Tao},
Title = {{Material footprint of a fast-industrializing region in China, Part 1:
   Exploring the materialization process of Liaoning Province}},
Journal = {{RESOURCES CONSERVATION AND RECYCLING}},
Year = {{2018}},
Volume = {{134}},
Pages = {{228-238}},
Month = {{JUL}},
Abstract = {{Liaoning Province is one of the most important industrial bases in China
   that is confronting the challenges of resource restriction during the
   rapid industrialization and urbanization process. To explore the
   materialization process on an economy, previous studies have focused on
   the Material Footprint (MF), a consumption-based indicator of resource
   use, at the national level, but few results are available at the
   subdivision level, especially in rapidly developing China. In this
   study, a Structural Decomposition Analysis (SDA) was conducted of the MF
   of Liaoning to understand the key drivers behind the consumption of raw
   materials. The results show that Liaoning's MF more than tripled, with
   an average annual growth rate of 13.4\%, rising from 534 Mt to 1880 Mt
   during 2002-2012. Among the four material categories, nonmetallic
   minerals dominated the MF by 55-77\% and contributed 833\% to the total
   increase. From a sectoral viewpoint, construction dominated the MF by
   65-85\% and accounted for 90.8\% of growth. In addition, among the four
   categories of final demand, investment played a prominent role in the
   MF, which more than quadrupled from 414 Mt (77.5\%) in 2002 to 1701 Mt
   (90.5\%) in 2012. The SDA results show that per capita final demand
   level was the strongest contributor, and that production structure was
   another chief contributor. In contrast, the significant improvement in
   material intensity and final demand composition played an important role
   in dematerialization of Liaoning. Optimizing investment towards less
   material-intensive sectors and designing mandatory targets for
   non-energy resources should be given more importance.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Wang, HM (Corresponding Author), Northeastern Univ, State Environm Protect Key Lab Ecoind, 11,Lane 3,Wen Hua Rd, Shenyang 110819, Liaoning, Peoples R China.
   Ma, Fengmei, Shenyang Agr Univ, Coll Econ \& Management, Shenyang 110866, Liaoning, Peoples R China.
   Wang, Heming; Wang, Jian; Zhao, Shen; Yue, Qiang; Du, Tao, Northeastern Univ, State Environm Protect Key Lab Ecoind, 11,Lane 3,Wen Hua Rd, Shenyang 110819, Liaoning, Peoples R China.
   Zhu, Bing; Chen, Dingjiang, Tsinghua Univ, Dept Chem Engn, Tsinghua Garden Rd 1, Beijing 100084, Peoples R China.
   Dai, Hancheng, Peking Univ, Coll Environm Sci \& Engn, Beijing 100871, Peoples R China.
   Zhang, Guangsheng, Liaoning Univ, Business Sch, Shenyang 110136, Liaoning, Peoples R China.
   Xie, Yang, Natl Inst Environm Studies, Ctr Social \& Environm Syst Res, 16-2 Onogawa, Tsukuba, Ibaraki 3058506, Japan.
   Geng, Yong, Shanghai Jiao Tong Univ, Sch Environm Sci \& Engn, 800 Dongchuan Rd, Shanghai 200240, Peoples R China.}},
DOI = {{10.1016/j.resconrec.2018.03.015}},
ISSN = {{0921-3449}},
EISSN = {{1879-0658}},
Keywords = {{Material footprint; Raw material consumption; Material flow analysis;
   Input-output analysis; Structural decomposition analysis; China}},
Keywords-Plus = {{STRUCTURAL DECOMPOSITION ANALYSIS; RAW-MATERIAL EQUIVALENTS;
   CARBON-DIOXIDE EMISSIONS; SOCIOECONOMIC DRIVERS; MATERIAL CONSUMPTION;
   RESOURCE USE; ENVIRONMENTAL PRESSURE; MAINLAND CHINA; SUSTAINABILITY;
   TRANSITIONS}},
Research-Areas = {{Engineering; Environmental Sciences \& Ecology}},
Web-of-Science-Categories  = {{Engineering, Environmental; Environmental Sciences}},
Author-Email = {{wangheming2006@gmail.com}},
ResearcherID-Numbers = {{Geng, Yong/B-6310-2018
   Ma, Fengmei/N-6372-2019
   Zhang, Guangsheng/I-5774-2015
   Dai, Hancheng/Y-8275-2019
   Wang, Heming/N-6430-2019
   }},
ORCID-Numbers = {{Geng, Yong/0000-0002-2284-1375
   Ma, Fengmei/0000-0002-3233-625X
   Zhang, Guangsheng/0000-0003-1482-9429
   Dai, Hancheng/0000-0003-4251-4707
   Wang, Heming/0000-0003-3487-0912
   Du, Tao/0000-0003-3021-0888
   Zhu, Bing/0000-0002-2890-7523}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71403175, 41401636, 41661144023, 71704005,
   51474067, 71690241, 71273179]; MOE (Ministry of Education of China)
   Project of Humanities and Social Sciences {[}13YJC790106, 13YJCZH172];
   China Postdoctoral Science FoundationChina Postdoctoral Science
   Foundation; Startup Research Fund of College of Environmental Science
   and Engineering at Peking University; Special Plan of Distinguished
   Professor of Liaoning Province; Innovation Team Support Plan of Liaoning
   Province {[}WT2015009]}},
Funding-Text = {{This research was supported by the National Natural Science Foundation
   of China (71403175, 41401636, 41661144023, 71704005, 51474067, 71690241
   and 71273179) MOE (Ministry of Education of China) Project of Humanities
   and Social Sciences (13YJC790106, 13YJCZH172), China Postdoctoral
   Science Foundation, the Startup Research Fund of College of
   Environmental Science and Engineering at Peking University, Special Plan
   of Distinguished Professor of Liaoning Province (2013), and Innovation
   Team Support Plan of Liaoning Province (WT2015009). We thank Prof.
   Zhongwu Lu for giving us the inspiration and Dr. Xin Tian for her
   valuable suggestion. We also appreciate the efforts of editor and
   anonymous reviewers.}},
Cited-References = {{Bringezu S., 2002, HDB IND ECOLOGY.
   BULLARD CW, 1975, ENERG POLICY, V3, P268, DOI 10.1016/0301-4215(75)90035-X.
   Central Committee of the Communist Party of China, 2011, CHIN 12 5 YEAR PLAN.
   Central Committee of the Communist Party of China, 2006, CHIN 11 5 YEAR PLAN.
   Central Committee of the Communist Party of China, 2016, CHIN 13 5 YEAR PLAN.
   Chen B, 2018, SCI TOTAL ENVIRON, V613, P931, DOI 10.1016/j.scitotenv.2017.09.138.
   Chen WQ, 2012, RESOUR CONSERV RECY, V65, P18, DOI 10.1016/j.resconrec.2012.05.003.
   Dietzenbacher E., 1998, ECON SYST RES, V10, P307, DOI DOI 10.1080/09535319800000023.
   Dietzenbacher E, 2006, J REGIONAL SCI, V46, P773, DOI 10.1111/j.1467-9787.2006.00477.x.
   Dittrich M., 2012, GREEN EC WORLD IMPLI.
   Editing Committee of China Agriculture Yearbook, 2009, CHIN AGR YB 2003 200.
   Editing Committee of China Agriculture Yearbook, 2014, CHIN AGR YB 2003 200.
   Editing Committee of China Agriculture Yearbook, 2004, CHIN AGR YB 2003 200.
   Editing Committee of China Energy Statistical Yearbook, 2009, CHIN EN STAT YB 2003.
   Editing Committee of China Energy Statistical Yearbook, 2004, CHIN EN STAT YB 2003.
   Editing Committee of China Energy Statistical Yearbook, 2014, CHIN EN STAT YB 2003.
   Editing Committee of China Steel Industry Yearbook, 2009, CHIN STEEL IND YB 20.
   Editing Committee of China Steel Industry Yearbook, 2014, CHIN STEEL IND YB 20.
   Editing Committee of China Steel Industry Yearbook, 2004, CHIN STEEL IND YB 20.
   Eisenmenger N, 2016, ECOL ECON, V128, P177, DOI 10.1016/j.ecolecon.2016.03.010.
   {*}EUR, 2001, EC WID MAT FLOW ACC.
   Eurostat, 2007, EC WID MAT FOW ACC C.
   Eurostat, 2013, EC WID MAT FLOW ACC.
   Feng KS, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms8714.
   Fischer-Kowalski M, 2011, J IND ECOL, V15, P855, DOI 10.1111/j.1530-9290.2011.00366.x.
   Geng Y, 2013, SCIENCE, V339, P1526, DOI 10.1126/science.1227059.
   Giljum S, 2015, J IND ECOL, V19, P792, DOI 10.1111/jiec.12214.
   Guan DB, 2014, ENVIRON SCI TECHNOL, V48, P11048, DOI 10.1021/es501379n.
   Guan DB, 2014, ENVIRON RES LETT, V9, DOI 10.1088/1748-9326/9/2/024010.
   Guan D, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2008GL036540.
   Hatfield-Dodds S, 2017, J CLEAN PROD, V144, P403, DOI 10.1016/j.jclepro.2016.12.170.
   Hertwich EG, 2005, ENVIRON SCI TECHNOL, V39, P4673, DOI 10.1021/es0497375.
   Hoekstra AY, 2014, SCIENCE, V344, P1114, DOI 10.1126/science.1248365.
   Hu MM, 2010, RESOUR CONSERV RECY, V54, P591, DOI 10.1016/j.resconrec.2009.10.016.
   Huang T, 2013, RESOUR CONSERV RECY, V72, P91, DOI 10.1016/j.resconrec.2012.12.013.
   Kagawa Shigemi, 2001, ECON SYST RES, V13, P339, DOI DOI 10.1080/09535310120089752.
   Kovanda J, 2013, ENVIRON SCI POLICY, V29, P71, DOI 10.1016/j.envsci.2013.01.005.
   Krausmann F, 2009, ECOL ECON, V68, P2696, DOI 10.1016/j.ecolecon.2009.05.007.
   Kucukvar M, 2017, RESOUR CONSERV RECY, V125, P251, DOI 10.1016/j.resconrec.2017.06.024.
   Lenzen M, 2012, ENVIRON SCI TECHNOL, V46, P8374, DOI 10.1021/es300171x.
   Lenzen M, 2009, ENVIRON SCI TECHNOL, V43, P8251, DOI 10.1021/es902090z.
   Liang S, 2016, ENVIRON SCI TECHNOL, V50, P7535, DOI 10.1021/acs.est.6b00872.
   Liang S, 2014, ENVIRON SCI TECHNOL, V48, P2807, DOI 10.1021/es500310t.
   Liang S, 2014, ENVIRON SCI TECHNOL, V48, P1103, DOI 10.1021/es4042429.
   Liu Q., 2010, CHINAS CONSTANT PRIC.
   Lu B, 2017, RESOUR CONSERV RECY, V119, P109, DOI 10.1016/j.resconrec.2016.05.015.
   Mi ZF, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa69cf.
   Miller R. E., 2009, INPUT OUTPUT ANAL FD.
   Ministry of Foreign Affairs of China, 2016, CHIN NAT PLAN IMPL 2.
   Ministry of Land and Resources of China, 2009, CHIN LAND RES STAT Y.
   Ministry of Land and Resources of China, 2014, CHIN LAND RES STAT Y.
   Ministry of Land and Resources of China, 2004, CHIN LAND RES STAT Y.
   Munoz P, 2009, J IND ECOL, V13, P881, DOI 10.1111/j.1530-9290.2009.00154.x.
   National Bureau of Statistics of China, 2016, CHIN STAT YB 2016.
   Ou JM, 2017, APPL ENERG, V204, P131, DOI 10.1016/j.apenergy.2017.06.112.
   Peters GP, 2007, ENVIRON SCI TECHNOL, V41, P5939, DOI 10.1021/es070108f.
   SCC, 2003, SEV OP REV STRAT OLD.
   Schaffartzik A, 2015, SUSTAINABILITY-BASEL, V7, P5345, DOI 10.3390/su7055345.
   Schandl H., 2016, GLOBAL MAT FLOWS RES.
   Schandl H, 2016, J CLEAN PROD, V132, P45, DOI 10.1016/j.jclepro.2015.06.100.
   Schandl H, 2010, J IND ECOL, V14, P533, DOI 10.1111/j.1530-9290.2010.00262.x.
   Schoer K, 2012, ENVIRON SCI TECHNOL, V46, P8903, DOI 10.1021/es300434c.
   State Council, 2018, BELT ROAD PORT.
   State Council, 2017, NOT STAT COUNC ISS O.
   State Forestry Bureau, 2009, CHIN FOR STAT YB 200.
   State Forestry Bureau, 2014, CHIN FOR STAT YB 200.
   State Forestry Bureau, 2004, CHIN FOR STAT YB 200.
   Su B, 2012, ENERG ECON, V34, P177, DOI 10.1016/j.eneco.2011.10.009.
   Su B, 2010, ENERG ECON, V32, P166, DOI 10.1016/j.eneco.2009.07.010.
   Survey from Liaoning Bureau of Statistics, 2017, INP OUTP TABL LIAON.
   Tian X, 2017, J CLEAN PROD, V142, P2114, DOI 10.1016/j.jclepro.2016.11.072.
   Tian X, 2014, APPL ENERG, V123, P19, DOI 10.1016/j.apenergy.2014.02.016.
   Tian X, 2014, ENVIRON SCI POLICY, V37, P243, DOI 10.1016/j.envsci.2013.10.001.
   Tian X, 2013, ENERG POLICY, V53, P279, DOI 10.1016/j.enpol.2012.10.054.
   UNDESASD, 1999, HDB INP OUTP TABL CO.
   UNEP, 2011, DECOUPLING NATURAL R.
   United Nations, 2015, TRANSF OUR WORLD 203.
   von Weizsacker E.U., 2014, DEC 2 TECHN OPP POL.
   Wang HM, 2013, RESOURCES-BASEL, V2, P270, DOI 10.3390/resources2030270.
   Wang HM, 2014, ENVIRON SCI TECHNOL, V48, P5025, DOI 10.1021/es405812w.
   Wang HM, 2012, J IND ECOL, V16, P481, DOI 10.1111/j.1530-9290.2012.00484.x.
   Wang T, 2016, J CLEAN PROD, V137, P752, DOI 10.1016/j.jclepro.2016.07.161.
   Weinzettel J, 2011, J IND ECOL, V15, P893, DOI 10.1111/j.1530-9290.2011.00378.x.
   West J., 2016, GREEN ASIA COUNTRY R.
   Wiedmann T, 2011, ECOL ECON, V70, P1937, DOI 10.1016/j.ecolecon.2011.06.014.
   Wiedmann TO, 2015, P NATL ACAD SCI USA, V112, P6271, DOI 10.1073/pnas.1220362110.
   Wood R, 2015, SUSTAINABILITY-BASEL, V7, P138, DOI 10.3390/su7010138.
   Xu M, 2002, ENERG POLICY, V39, P7381.
   Xu M., 2008, ENVIRON SCI TECHNOL, V42, P7.
   Xu M, 2008, RESOUR CONSERV RECY, V52, P1082, DOI 10.1016/j.resconrec.2008.04.007.
   Xu M, 2007, J IND ECOL, V11, P121, DOI 10.1162/jiec.2007.1105.
   Yu YD, 2015, ECOL ECON, V118, P123, DOI 10.1016/j.ecolecon.2015.07.019.}},
Number-of-Cited-References = {{92}},
Times-Cited = {{5}},
Usage-Count-Last-180-days = {{2}},
Usage-Count-Since-2013 = {{35}},
Journal-ISO = {{Resour. Conserv. Recycl.}},
Doc-Delivery-Number = {{GH2XT}},
Unique-ID = {{ISI:000433266000026}},
DA = {{2020-08-06}},
}

@article{ ISI:000442579700017,
Author = {Hong, Siyang and Wang, Hongrui and Cheng, Tao},
Title = {{Circulation Characteristic Analysis of Implied Water Flow Based on a
   Complex Network: A Case Study for Beijing, China}},
Journal = {{WATER}},
Year = {{2018}},
Volume = {{10}},
Number = {{7}},
Month = {{JUL}},
Abstract = {{Water and energy are two indispensable resources in national economic
   production. Water is circulated among economic sectors through products
   or services; however, indirect water consumption calculated by the input
   output method fails to reflect the implied water utilised during energy
   consumption. This study combined the ecological input output method with
   a complex network model to analyse the embodied energy intensity (EEI)
   and the implied water intensity of embodied energy (IWIEE), and then
   constructed and analysed the implied water circulation network (IWCN) of
   40 sectors in 2007, 2010, and 2012 in Beijing. The results indicate that
   the energy consumption of all of the sectors is mainly embodied in the
   transfer of the external provinces of China, and the variation trend of
   the implied water intensity of the embodied energy is consistent with
   the embodied energy intensity. The implied water circulation networks
   had small-world characteristics, indicating that water-saving effects in
   key sectors can quickly spread to other sectors. However, this may also
   result in a corresponding negative impact if water shortages occur in
   these sectors, due to the same spreading effect. The node strength,
   eigenvector centrality, key edge, and key indirect water flow path were
   selected as indicators to measure key sectors. Finally, water-saving
   measures and suggestions were proposed according to the complex network
   characteristics.}},
Publisher = {{MDPI}},
Address = {{ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Wang, HR (Corresponding Author), Beijing Normal Univ, Coll Water Sci, Beijing Key Lab Urban Hydrol Cycle \& Sponge City, 19 Xinjiekou Rd, Beijing 100875, Peoples R China.
   Hong, Siyang; Wang, Hongrui; Cheng, Tao, Beijing Normal Univ, Coll Water Sci, Beijing Key Lab Urban Hydrol Cycle \& Sponge City, 19 Xinjiekou Rd, Beijing 100875, Peoples R China.}},
DOI = {{10.3390/w10070834}},
Article-Number = {{834}},
EISSN = {{2073-4441}},
Keywords = {{complex network; ecological input-output method; embodied energy
   intensity; implied water of embodied energy; Beijing}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; INTERNATIONAL OIL TRADE; EMBODIED ENERGY;
   WORLD-ECONOMY; INDUSTRIAL SECTORS; RESOURCES USE; EXERGY FLOW;
   EVOLUTION; CONSUMPTION; EMISSIONS}},
Research-Areas = {{Water Resources}},
Web-of-Science-Categories  = {{Water Resources}},
Author-Email = {{hongsy@mail.bnu.edu.cn
   henrywang@bnu.edu.cn
   tao\_cheng@mail.bnu.edu.cn}},
ORCID-Numbers = {{Cheng, Tao/0000-0002-5204-3470}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}51479003]}},
Funding-Text = {{This research was funded by the National Natural Science Foundation of
   China {[}The integrated model of distinguishing drought and water
   scarcity and its application based on time-varying Copula] grant number
   {[}51479003].{''}}},
Cited-References = {{An Q, 2015, ECOL MODEL, V318, P26, DOI 10.1016/j.ecolmodel.2015.01.020.
   Avrin AP, 2015, DESALINATION, V360, P1, DOI 10.1016/j.desal.2014.12.028.
   Barabasi AL, 1999, SCIENCE, V286, P509, DOI 10.1126/science.286.5439.509.
   Beijing Municipal Water Affairs Bureau, 2013, BEIJ MUN WAT AFF BUR.
   Beijing Municipal Water Affairs Bureau, 2011, BEIJ MUN WAT AFF BUR.
   Beijing Municipal Water Affairs Bureau, 2016, BEIJ MUN WAT AFF BUR.
   Beijing Municipal Water Affairs Bureau, 2008, BEIJ MUN WAT AFF BUR.
   Beijing Statistical Bureau (BSB), 2009, INP OUTP TABL BEIJ E.
   Beijing Statistical Bureau (BSB), 2011, BEIJ STAT YB 2007 20.
   Beijing Statistical Bureau (BSB), 2012, INP OUTP TABL BEIJ E.
   Beijing Statistical Bureau (BSB), 2013, BEIJ STAT YB 2007 20.
   Beijing Statistical Bureau (BSB), 2008, BEIJ STAT YB 2007 20.
   BSB, 2014, INP OUTP TABL BEIJ E.
   Cellura M, 2011, RENEW SUST ENERG REV, V15, P3897, DOI 10.1016/j.rser.2011.07.025.
   Chen B, 2018, APPL ENERG, V210, P98, DOI 10.1016/j.apenergy.2017.10.113.
   Chen GQ, 2017, RENEW SUST ENERG REV, V69, P735, DOI 10.1016/j.rser.2016.11.151.
   Chen GQ, 2011, ECOL MODEL, V222, P2362, DOI 10.1016/j.ecolmodel.2010.11.024.
   Chen GQ, 2010, ENERG POLICY, V38, P6180, DOI 10.1016/j.enpol.2010.06.004.
   Chen GQ, 2011, COMMUN NONLINEAR SCI, V16, P583, DOI 10.1016/j.cnsns.2010.02.026.
   Chen GQ, 2010, COMMUN NONLINEAR SCI, V15, P3647, DOI 10.1016/j.cnsns.2009.12.024.
   Chen ZM, 2010, PROCEDIA ENVIRON SCI, V2, P1827, DOI 10.1016/j.proenv.2010.10.194.
   Chen ZM, 2010, COMMUN NONLINEAR SCI, V15, P1942, DOI 10.1016/j.cnsns.2009.08.001.
   Chen ZM, 2013, ECOL INDIC, V28, P142, DOI 10.1016/j.ecolind.2012.07.024.
   Chen ZH, 2016, J NAT GAS SCI ENG, V33, P769, DOI 10.1016/j.jngse.2016.06.022.
   Dalin C, 2014, P NATL ACAD SCI USA, V111, P9774, DOI 10.1073/pnas.1404749111.
   Davis G. F., 2003, Strategic Organization, V1, P301, DOI 10.1177/14761270030013002.
   Du RJ, 2017, APPL ENERG, V196, P142, DOI 10.1016/j.apenergy.2016.12.042.
   Gao CX, 2015, APPL ENERG, V156, P542, DOI 10.1016/j.apenergy.2015.07.054.
   Geng JB, 2014, APPL ENERG, V132, P23, DOI 10.1016/j.apenergy.2014.06.064.
   Hao XQ, 2016, APPL ENERG, V162, P1515, DOI 10.1016/j.apenergy.2015.04.032.
   Kucukvar M, 2014, J CLEAN PROD, V81, P234, DOI 10.1016/j.jclepro.2014.06.033.
   Kuhtz S, 2010, ENERGY, V35, P364, DOI 10.1016/j.energy.2009.10.002.
   Li HN, 2011, PROCEDIA ENVIRON SCI, V11, P824, DOI 10.1016/j.proenv.2011.12.126.
   Li H, 2016, ENRGY PROCED, V104, P118, DOI 10.1016/j.egypro.2016.12.021.
   Li JS, 2014, RENEW SUST ENERG REV, V34, P642, DOI 10.1016/j.rser.2014.03.038.
   Liu SY, 2017, J CLEAN PROD, V156, P962, DOI 10.1016/j.jclepro.2017.04.083.
   Liu X, 2018, J CLEAN PROD, V172, P724, DOI 10.1016/j.jclepro.2017.10.238.
   Miller R. E, 1985, INPUT OUTPUT ANAL FD, P1293.
   National Bureau of Statistics (NSB), 2009, INP OUTP TABL CHIN E.
   National Bureau of Statistics (NSB), 2011, CHIN EN STAT YB 2007.
   National Bureau of Statistics (NSB), 2008, CHIN EN STAT YB 2007.
   National Bureau of Statistics (NSB), 2018, CHIN EN STAT YB 2017.
   National Bureau of Statistics (NSB), 2013, CHIN EN STAT YB 2007.
   National Bureau of Statistics (NSB), 2011, CHIN ENV STAT YB 200.
   National Bureau of Statistics (NSB), 2013, CHIN ENV STAT YB 200.
   National Bureau of Statistics (NSB), 2012, INP OUTP TABL CHIN E.
   National Bureau of Statistics (NSB), 2008, CHIN ENV STAT YB 200.
   Newman MEJ, 2003, SIAM REV, V45, P167, DOI 10.1137/S003614450342480.
   Parand FA, 2016, PHYSICA A, V459, P24, DOI 10.1016/j.physa.2016.03.079.
   Sartori M, 2017, ADV WATER RESOUR, V110, P538, DOI 10.1016/j.advwatres.2017.05.005.
   Shao L, 2014, MULTISCALE INPUT OUT.
   Shao L, 2017, J CLEAN PROD, V164, P338, DOI 10.1016/j.jclepro.2017.06.117.
   Shao L, 2016, J CLEAN PROD, V112, P4628, DOI 10.1016/j.jclepro.2015.06.096.
   Sun CW, 2018, ENERG POLICY, V113, P643, DOI 10.1016/j.enpol.2017.11.055.
   Sun XQ, 2018, J CLEAN PROD, V174, P548, DOI 10.1016/j.jclepro.2017.10.228.
   Sun XQ, 2016, ENERGY, V94, P195, DOI 10.1016/j.energy.2015.10.102.
   Wang XB, 2017, RESOUR CONSERV RECY, V125, P363, DOI 10.1016/j.resconrec.2017.07.006.
   Watts DJ, 1998, NATURE, V393, P440, DOI 10.1038/30918.
   Wu XD, 2016, APPL ENERG, V184, P936, DOI 10.1016/j.apenergy.2016.03.027.
   Yang Y, 2015, ENERGY, V93, P534, DOI 10.1016/j.energy.2015.09.079.
   Ye QL, 2018, WATER RES, V129, P264, DOI 10.1016/j.watres.2017.11.036.
   Zhang LX, 2017, J CLEAN PROD, V142, P829, DOI 10.1016/j.jclepro.2016.03.063.
   Zhong WQ, 2014, PHYSICA A, V413, P42, DOI 10.1016/j.physa.2014.06.055.
   Zhou SY, 2010, COMMUN NONLINEAR SCI, V15, P3201, DOI 10.1016/j.cnsns.2009.11.026.}},
Number-of-Cited-References = {{64}},
Times-Cited = {{0}},
Usage-Count-Last-180-days = {{2}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Water}},
Doc-Delivery-Number = {{GR4LJ}},
Unique-ID = {{ISI:000442579700017}},
OA = {{DOAJ Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000446670800012,
Author = {Jin, Dachao and Huo, Liwei},
Title = {{Influence of tropical Atlantic sea surface temperature anomalies on the
   East Asian summer monsoon}},
Journal = {{QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY}},
Year = {{2018}},
Volume = {{144}},
Number = {{714, A}},
Pages = {{1490-1500}},
Month = {{JUL}},
Abstract = {{This study investigates the relationship between tropical Atlantic (TA)
   sea surface temperature (SST) anomalies and the East Asian summer
   monsoon (EASM), as well as the possible mechanism by which TA SST
   anomalies affect the EASM. We demonstrate a robust positive simultaneous
   correlation between the boreal summer TA SST anomalies and the EASM.
   Observational and model-based studies identify an atmospheric
   teleconnection in which the summer TA warming can enhance convection and
   induce low-level convergence in the Atlantic basin, which alters the
   Walker circulation and produces a sinking motion and divergence in the
   central Pacific. As a Rossby response to the anomalous divergence, an
   anomalous anticyclonic pair is generated over the western Pacific. As a
   result, the EASM is strengthened. Additionally, a significant lag
   correlation of the EASM with TA SST anomalies from the previous boreal
   spring is demonstrated, which implies potential applicability of the TA
   SST factor to the EASM prediction at seasonal time-scales.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Huo, LW (Corresponding Author), Nanjing Univ Informat Sci \& Technol, CIC FEMD, Nanjing 210044, Jiangsu, Peoples R China.
   Huo, LW (Corresponding Author), Nanjing Univ Informat Sci \& Technol, KLME, ILCEC, Nanjing 210044, Jiangsu, Peoples R China.
   Nanjing Univ Informat Sci \& Technol, Key Lab Meteorol Disaster, Minist Educ KLME, Joint Int Res Lab Climate \& Environm Change ILCE, Nanjing, Jiangsu, Peoples R China.
   Huo, Liwei, Nanjing Univ Informat Sci \& Technol, CIC FEMD, Nanjing 210044, Jiangsu, Peoples R China.}},
DOI = {{10.1002/qj.3296}},
ISSN = {{0035-9009}},
EISSN = {{1477-870X}},
Keywords = {{East Asian summer monsoon; sea surface temperature anomalies; tropical
   Atlantic}},
Keywords-Plus = {{COMMUNITY ATMOSPHERE MODEL; WESTERN NORTH PACIFIC; EL-NINO; ENSO
   RELATIONSHIP; INTERANNUAL VARIABILITY; OCEAN CAPACITOR; CLIMATE;
   OSCILLATION; CIRCULATION; RAINFALL}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{huolw@nuist.edu.cn}},
Funding-Acknowledgement = {{Natural Science Foundation of Jiangsu Province of ChinaNatural Science
   Foundation of Jiangsu Province {[}BK20160956]; Natural Science
   Foundation of ChinaNational Natural Science Foundation of China
   {[}41330425]; Priority Academic Program Development of Jiangsu Higher
   Education Institutions (PAPD); Startup Foundation for Introducing Talent
   of NUIST {[}2015r035, 2014r006]; General Program of the Natural Science
   Foundation of Jiangsu Higher Education Institutions {[}17KJB170013]}},
Funding-Text = {{Natural Science Foundation of Jiangsu Province of China, BK20160956.
   Natural Science Foundation of China, 41330425. Priority Academic Program
   Development of Jiangsu Higher Education Institutions (PAPD), and the
   Startup Foundation for Introducing Talent of NUIST, 2015r035, 2014r006.
   General Program of the Natural Science Foundation of Jiangsu Higher
   Education Institutions, 17KJB170013.}},
Cited-References = {{Adler RF, 2003, J HYDROMETEOROL, V4, P1147, DOI 10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.
   Alexander M, 2002, GEOPHYS RES LETT, V29, DOI 10.1029/2001GL014347.
   Alexander MA, 2002, J CLIMATE, V15, P2205, DOI 10.1175/1520-0442(2002)015<2205:TABTIO>2.0.CO;2.
   Ashok K, 2007, J GEOPHYS RES-OCEANS, V112, DOI 10.1029/2006JC003798.
   Bretherton CS, 2008, J ATMOS SCI, V65, P2174, DOI 10.1175/2007JAS2242.1.
   Bretherton CS, 2009, J CLIMATE, V22, P3422, DOI 10.1175/2008JCLI2556.1.
   Chang P, 2006, NATURE, V443, P324, DOI 10.1038/nature05053.
   Chen SF, 2015, J CLIMATE, V28, P485, DOI 10.1175/JCLI-D-14-00422.1.
   Chen W, 2014, J GEOPHYS RES-ATMOS, V119, P13637, DOI 10.1002/2014JD022199.
   Chiang JCH, 2002, J CLIMATE, V15, P2616, DOI 10.1175/1520-0442(2002)015<2616:TTTVCB>2.0.CO;2.
   Chikamoto Y, 2016, GEOPHYS RES LETT, V43, P7143, DOI 10.1002/2016GL069544.
   Ding H, 2012, CLIM DYNAM, V38, P1965, DOI 10.1007/s00382-011-1097-y.
   Ding YH, 2005, METEOROL ATMOS PHYS, V89, P117, DOI 10.1007/s00703-005-0125-z.
   Du Y, 2009, J CLIMATE, V22, P2023, DOI 10.1175/2008JCLI2590.1.
   Feng J, 2014, J CLIMATE, V27, P2682, DOI 10.1175/JCLI-D-13-00015.1.
   GILL AE, 1980, Q J ROY METEOR SOC, V106, P447, DOI 10.1256/smsqj.44904.
   Ham YG, 2013, NAT GEOSCI, V6, P112, DOI {[}10.1038/NGEO1686, 10.1038/ngeo1686].
   Hong CC, 2015, CLIM DYNAM, V45, P633, DOI 10.1007/s00382-014-2275-5.
   Hong CC, 2014, J GEOPHYS RES-ATMOS, V119, P3715, DOI 10.1002/2013JD021394.
   Huang RH, 2012, ADV ATMOS SCI, V29, P910, DOI 10.1007/s00376-012-2015-x.
   Huo LW, 2015, GEOPHYS RES LETT, V42, P2378, DOI 10.1002/2015GL063184.
   HURRELL JW, 1995, SCIENCE, V269, P676, DOI 10.1126/science.269.5224.676.
   Jin DC, 2013, J CLIMATE, V26, P8210, DOI 10.1175/JCLI-D-12-00652.1.
   Kalnay E, 1996, B AM METEOROL SOC, V77, P437, DOI 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.
   Kao HY, 2009, J CLIMATE, V22, P615, DOI 10.1175/2008JCLI2309.1.
   Keenlyside NS, 2013, GEOPHYS RES LETT, V40, P2278, DOI 10.1002/grl.50362.
   Keenlyside NS, 2007, J CLIMATE, V20, P131, DOI 10.1175/JCLI3992.1.
   Kucharski F, 2007, J CLIMATE, V20, P4255, DOI 10.1175/JCLI4254.1.
   Kucharski F, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2007GL033037.
   Kucharski F, 2009, Q J ROY METEOR SOC, V135, P569, DOI 10.1002/qj.406.
   Kucharski F, 2016, CLIM DYNAM, V46, P2337, DOI 10.1007/s00382-015-2705-z.
   Kug JS, 2009, J CLIMATE, V22, P1499, DOI 10.1175/2008JCLI2624.1.
   Li JP, 2003, ADV ATMOS SCI, V20, P661.
   Lin SJ, 2004, MON WEATHER REV, V132, P2293, DOI 10.1175/1520-0493(2004)132<2293:AVLFDC>2.0.CO;2.
   Losada T, 2010, CLIM DYNAM, V35, P45, DOI 10.1007/s00382-009-0624-6.
   Lu RY, 2005, J GEOPHYS RES-ATMOS, V110, DOI 10.1029/2004JD005676.
   Martin-Rey M, 2012, SCI MAR, V76, P105, DOI 10.3989/scimar.03610.19A.
   Matsuno T., 1966, J METEOR SOC JAPAN, V44, P25, DOI {[}DOI 10.2151/JMSJ1965.44.1\_25, 10.2151/jmsj1965.44.1\_25].
   Mlawer EJ, 1997, J GEOPHYS RES-ATMOS, V102, P16663, DOI 10.1029/97JD00237.
   Morrison H, 2008, J CLIMATE, V21, P3642, DOI 10.1175/2008JCLI2105.1.
   Neale R. B., 2012, DESCRIPTION NCAR COM.
   Polo I, 2015, CLIM DYNAM, V44, P115, DOI 10.1007/s00382-014-2354-7.
   Rajeevan M, 2008, GEOPHYS RES LETT, V35, DOI 10.1029/2008GL036025.
   Rayner NA, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2002JD002670.
   Richter JH, 2008, J CLIMATE, V21, P1487, DOI 10.1175/2007JCLI1789.1.
   Rodriguez-Fonseca B, 2009, GEOPHYS RES LETT, V36, DOI 10.1029/2009GL040048.
   Rong XY, 2010, CHINESE SCI BULL, V55, P2458, DOI 10.1007/s11434-010-3098-3.
   Sampe T, 2010, J CLIMATE, V23, P113, DOI 10.1175/2009JCLI3128.1.
   SIMMONS AJ, 1981, MON WEATHER REV, V109, P758, DOI 10.1175/1520-0493(1981)109<0758:AEAAMC>2.0.CO;2.
   Srivastava AK, 2002, GEOPHYS RES LETT, V29, DOI 10.1029/2001GL013837.
   Tao SY, 1987, MONSOON METEOROLOGY, P60, DOI DOI 10.16175/J.CNKI.1009-4229.2011.11.012.
   Wang B, 2000, J CLIMATE, V13, P1517, DOI 10.1175/1520-0442(2000)013<1517:PEATHD>2.0.CO;2.
   Wang B, 1999, B AM METEOROL SOC, V80, P629, DOI 10.1175/1520-0477(1999)080<0629:COSASM>2.0.CO;2.
   Wang B, 2008, J CLIMATE, V21, P4449, DOI 10.1175/2008JCLI2183.1.
   Wang CZ, 2006, GEOPHYS RES LETT, V33, DOI 10.1029/2006GL026324.
   Wu CH, 2016, J CLIMATE, V29, P4445, DOI 10.1175/JCLI-D-15-0594.1.
   Wu RG, 2012, THEOR APPL CLIMATOL, V108, P119, DOI 10.1007/s00704-011-0519-4.
   Wu RG, 2003, J CLIMATE, V16, P3742, DOI 10.1175/1520-0442(2003)016\<3742:EOERAI\>2.0.CO;2.
   Wu RG, 2002, J CLIMATE, V15, P3266, DOI 10.1175/1520-0442(2002)015<3266:ACOTEA>2.0.CO;2.
   Wu ZW, 2009, J GEOPHYS RES-ATMOS, V114, DOI 10.1029/2009JD011733.
   Xie SP, 2016, ADV ATMOS SCI, V33, P411, DOI 10.1007/s00376-015-5192-6.
   Xie SP, 2009, J CLIMATE, V22, P730, DOI 10.1175/2008JCLI2544.1.
   ZHANG GJ, 1995, ATMOS OCEAN, V33, P407, DOI 10.1080/07055900.1995.9649539.}},
Number-of-Cited-References = {{63}},
Times-Cited = {{9}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Q. J. R. Meteorol. Soc.}},
Doc-Delivery-Number = {{GW1VW}},
Unique-ID = {{ISI:000446670800012}},
OA = {{Other Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000445150300015,
Author = {Engel, Max and Boesl, Fabian and Brueckner, Helmut},
Title = {{Migration of Barchan Dunes in Qatar-Controls of the Shamal,
   Teleconnections, Sea-Level Changes and Human Impact}},
Journal = {{GEOSCIENCES}},
Year = {{2018}},
Volume = {{8}},
Number = {{7}},
Month = {{JUL}},
Abstract = {{Barchan dune fields are a dominant landscape feature in SE Qatar and a
   key element of the peninsula's geodiversity. The migration of barchan
   dunes is mainly controlled by dune size, wind patterns, vegetation cover
   and human impact. We investigate the variability of dune migration in
   Qatar over a time period of 50 years using high-resolution satellite and
   aerial imagery. We then explore its relation to the regional Shamal wind
   system, teleconnection patterns, and limitations in sand supply
   associated with the transgression of the Arabian Gulf. Strong
   size-dependent differences in migration rates of individual dunes as
   well as significant decadal variability on a dune-field scale are
   detected, which are found to correlate with the intensity of the North
   Atlantic Oscillation (NAO) and the Indian Summer Monsoon (ISM), in
   particular during years of relatively strong (weak) summer Shamals. High
   uncertainties associated with the extrapolation of migration rates back
   into the Holocene, however, do not permit further examination of the
   timing of the loss of sand supply and the onset of the mid-Holocene
   relative sea-level (RSL) highstand. For the youngest phase considered in
   this study (2006-2015), human impact has likely accelerated dune
   migration under a weakening Shamal regime through sand mining and
   excessive vehicle traffic upwind of the core study area.}},
Publisher = {{MDPI}},
Address = {{ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Engel, M (Corresponding Author), Geol Survey Belgium, Royal Belgian Inst Nat Sci, OD Earth \& Hist Life, Jennerstr 13, B-1000 Brussels, Belgium.
   Engel, Max, Geol Survey Belgium, Royal Belgian Inst Nat Sci, OD Earth \& Hist Life, Jennerstr 13, B-1000 Brussels, Belgium.
   Boesl, Fabian; Brueckner, Helmut, Univ Cologne, Inst Geog, Zulpicher Str 45, D-50674 Cologne, Germany.}},
DOI = {{10.3390/geosciences8070240}},
Article-Number = {{UNSP 240}},
ISSN = {{2076-3263}},
Keywords = {{Aeolian geomorphology; Arabian Peninsula; Arabian/Persian Gulf; remote
   sensing; Holocene landscape change}},
Keywords-Plus = {{ARABIAN GULF; SAUDI-ARABIA; SAND-DUNES; ARABIAN/PERSIAN GULF; ATLANTIC
   OSCILLATION; SURFACE PRESSURE; DUST STORMS; DESERT SAND; MIDDLE-EAST;
   HOLOCENE}},
Research-Areas = {{Geology}},
Web-of-Science-Categories  = {{Geosciences, Multidisciplinary}},
Author-Email = {{max.engel@naturalsciences.be
   fabian.boesl@gmx.de
   h.brueckner@uni-koeln.de}},
ResearcherID-Numbers = {{Engel, Max/H-1818-2011
   }},
ORCID-Numbers = {{Engel, Max/0000-0002-2271-4229
   Boesl, Fabian/0000-0003-4650-6149}},
Funding-Acknowledgement = {{South Qatar Survey Project (SQSP); Max Delbruck Prize {[}DFG ZUK 81/1]}},
Funding-Text = {{Funding of fieldwork-conducted in the framework of the South Qatar
   Survey Project (SQSP)
   (https://fallback.dainst.org/projekt/-/project-display/612902)-and
   logistic support by Qatar Museums (QM) and the Orient Department of the
   German Archaeological Institute (DAI) is gratefully acknowledged.
   Permissions for the field survey were issued by QM. Gambit, Hexagon,
   IKONOS and aerial ortho-imagery were kindly provided by QM, DAI and the
   Qatar National Historic Environment Record Project (QNHER). Additional
   funding of personnel costs and commercial satellite imagery was provided
   through a Max Delbruck Prize, junior category (Zukunftskonzept
   Universitat zu Koln, DFG ZUK 81/1), awarded to M.E.}},
Cited-References = {{Al Senafi F, 2015, INT J CLIMATOL, V35, P4509, DOI 10.1002/joc.4302.
   Al-Ansary M, 2012, INT J SUSTAIN BUILT, V1, P64, DOI DOI 10.1016/J.IJSBE.2012.07.001.
   Al-Saad H, 2005, J ASIAN EARTH SCI, V25, P781, DOI 10.1016/j.jseaes.2004.07.009.
   Al-Yousef M., 2003, THESIS.
   ALHINAI KG, 1987, INT J REMOTE SENS, V8, P251, DOI 10.1080/01431168708948639.
   Anderson RS, 1996, NATURE, V379, P24, DOI 10.1038/379024a0.
   Bagnold R.A., 1941, PHYS BLOWN SAND DESE.
   BANSOD SD, 1995, THEOR APPL CLIMATOL, V51, P59, DOI 10.1007/BF00865540.
   Barth HJ, 2001, J ARID ENVIRON, V47, P387, DOI 10.1006/jare.2000.0668.
   Bartlett KS., 2004, THESIS.
   Ben-Gai T, 2001, THEOR APPL CLIMATOL, V69, P171, DOI 10.1007/s007040170023.
   BESLER H, 1997, PHYS BL, V53, P983.
   Breed C.S., 1979, STUDY GLOBAL SAND SE, P253.
   Bubenzer O., 2010, TOPICS INTERDISCIPLI, V15, P23.
   Cullen HM, 2000, INT J CLIMATOL, V20, P853, DOI 10.1002/1097-0088(20000630)20:8\<853::AID-JOC497\>3.0.CO;2-M.
   Doornkamp J.C., 1980, GEOLOGY GEOMORPHOLOG, P443.
   Edgell H.S., 2006, ARABINA DESERTS NATU, P187.
   EMBABI NS, 1993, J ARID ENVIRON, V25, P49, DOI 10.1006/jare.1993.1042.
   Engel M., 2014, Z ORIENT ARCHAOLOGIE, V7, P290.
   Engel M, 2012, QUATERN INT, V266, P131, DOI 10.1016/j.quaint.2011.04.028.
   Farr TG, 2007, REV GEOPHYS, V45, DOI 10.1029/2005RG000183.
   Fleitmann D, 2007, QUATERNARY SCI REV, V26, P170, DOI 10.1016/j.quascirev.2006.04.012.
   Gillette D. A., 1983, Environmental effects of off-road vehicles. Impacts and management of arid regions, P97.
   Glennie KW, 2002, QUATERNARY SCI REV, V21, P853, DOI 10.1016/S0277-3791(01)00133-0.
   Govinda Rao P., 2003, Weather, V58, P471.
   Hamidi M, 2013, ASIA-PAC J ATMOS SCI, V49, P279, DOI 10.1007/s13143-013-0027-9.
   Hersen P, 2004, PHYS REV E, V69, DOI 10.1103/PhysRevE.69.011304.
   Hesp PA, 1998, GEOMORPHOLOGY, V22, P193, DOI 10.1016/S0169-555X(97)00070-6.
   Hesse R, 2009, GEOMORPHOLOGY, V104, P185, DOI 10.1016/j.geomorph.2008.08.006.
   Kassler P., 1973, PERSIAN GULF, P11, DOI DOI 10.1007/978-3-642-65545-6.
   Lambeck K, 1996, EARTH PLANET SC LETT, V142, P43, DOI 10.1016/0012-821X(96)00069-6.
   Lancaster N, 1998, EARTH SURF PROC LAND, V23, P69, DOI 10.1002/(SICI)1096-9837(199801)23:1\<69::AID-ESP823\>3.0.CO;2-G.
   Livingstone I, 2007, EARTH-SCI REV, V80, P239, DOI 10.1016/j.earscirev.2006.09.004.
   Lokier SW, 2015, QUATERNARY RES, V84, P69, DOI 10.1016/j.yqres.2015.04.007.
   Matter A, 2015, QUATERN INT, V382, P120, DOI 10.1016/j.quaint.2014.12.029.
   MIDDLETON NJ, 1986, J CLIMATOL, V6, P183, DOI 10.1002/joc.3370060207.
   NWS (National Weather Service), N ATL OSC NAO.
   Parker AG, 2008, GEOMORPHOLOGY, V101, P458, DOI 10.1016/j.geomorph.2007.04.028.
   Parteli EJR, 2007, PHYS REV E, V75, DOI 10.1103/PhysRevE.75.011301.
   Perthuisot J.P., 1977, B SOC GEOL FR, P1167.
   Puls D.D., 2009, P INT PETR TECHN C D, V3, P1799.
   Rao P. G., 2001, WEATHER, V56, P444, DOI {[}DOI 10.1002/J.1477-8696.2001.TB06528.X, 10.1002/j.1477-8696.2001.tb06528.x].
   Reinink-Smith LM, 2015, QUATERNARY RES, V84, P200, DOI 10.1016/j.yqres.2015.06.005.
   Rimbu N, 2003, GEOPHYS RES LETT, V30, DOI 10.1029/2002GL016570.
   Sadiq A, 2009, REMOTE SENS-BASEL, V1, P915, DOI 10.3390/rs1040915.
   Saeed S, 2011, CLIM DYNAM, V37, P1045, DOI 10.1007/s00382-010-0888-x.
   SHINN EA, 1973, PERSIAN GULF, P179.
   Strohmenger C. J., 2015, 1 BREAK, V33, P41, DOI DOI 10.3997/1365-2397.2014027.
   Thomas DSG, 2005, NATURE, V435, P1218, DOI 10.1038/nature03717.
   Vermeesch P, 2012, GEOPHYS RES LETT, V39, DOI 10.1029/2012GL052592.
   Wang B, 1999, B AM METEOROL SOC, V80, P629, DOI 10.1175/1520-0477(1999)080<0629:COSASM>2.0.CO;2.
   Weatherall P, 2015, EARTH SPACE SCI, V2, P331, DOI 10.1002/2015EA000107.
   Wiggs G.F.S., 2013, TREATISE GEOMORPHOLO, V11, P201.
   Yizhaq H, 2009, J GEOPHYS RES-EARTH, V114, DOI 10.1029/2008JF001138.
   Yu Y, 2016, J GEOPHYS RES-ATMOS, V121, P289, DOI 10.1002/2015JD024063.}},
Number-of-Cited-References = {{55}},
Times-Cited = {{1}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{2}},
Journal-ISO = {{Geosciences}},
Doc-Delivery-Number = {{GU3BZ}},
Unique-ID = {{ISI:000445150300015}},
OA = {{DOAJ Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000441830500265,
Author = {Mikulic, Davor and Lovrincevic, Zeljko and Kecek, Damira},
Title = {{Economic Effects of Wind Power Plant Deployment on the Croatian Economy}},
Journal = {{ENERGIES}},
Year = {{2018}},
Volume = {{11}},
Number = {{7}},
Month = {{JUL}},
Abstract = {{This paper tests the hypothesis that incentives for renewable energy
   sources contribute to economic development in Croatia. The aim of the
   paper is to quantify the total effects of wind power plant deployment on
   the Croatian economy in terms of employment and gross value. Indirect
   and induced effects are spread over the value added chain of producers
   of investment and intermediate goods and services required for wind
   power plant deployment and operation. The open input-output model is
   used for quantifying indirect effects. The closed input output model,
   which assumes endogenous personal consumption, is applied for
   quantifying total effects, which includes the effects of induced
   personal consumption. The gross value added and employment type I and
   type II multipliers related to wind power plants in Croatia were
   calculated separately for the investment and intermediate consumption
   channel. The results show positive indirect and induced effects relating
   to the deployment of wind power plants in Croatia. They are less
   pronounced in comparison to previous studies due to the undeveloped
   domestic production of equipment required for wind power plant
   deployment. Apart from the manufacturing sector, which produces
   equipment incorporated into wind power plants, the total effects were
   significant for construction, transport, and other supporting
   industries.}},
Publisher = {{MDPI}},
Address = {{ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Mikulic, D (Corresponding Author), Inst Econ Zagreb, Zagreb 10000, Croatia.
   Mikulic, Davor; Lovrincevic, Zeljko, Inst Econ Zagreb, Zagreb 10000, Croatia.
   Kecek, Damira, Univ North, Univ Ctr Varazdin, Varazhdin 42000, Croatia.}},
DOI = {{10.3390/en11071881}},
Article-Number = {{UNSP 1881}},
ISSN = {{1996-1073}},
Keywords = {{wind power plants; input-output analysis; gross value added; employment;
   Croatia}},
Keywords-Plus = {{RENEWABLE ENERGY; EMPLOYMENT; IMPACTS}},
Research-Areas = {{Energy \& Fuels}},
Web-of-Science-Categories  = {{Energy \& Fuels}},
Author-Email = {{dmikulic@eizg.hr
   zlovrincevic@eizg.hr
   dkecek@unin.hr}},
ResearcherID-Numbers = {{Mikulic, Davor/AAA-2279-2020
   }},
ORCID-Numbers = {{Mikulic, Davor/0000-0002-9847-6116
   Kecek, Damira/0000-0003-1555-3655
   Lovrincevic, Zeljko/0000-0002-5052-297X}},
Cited-References = {{Armeanu DS, 2017, ENERGIES, V10, DOI 10.3390/en10030381.
   Belegri-Roboli A., 2010, P 31 ANN C INT WORK.
   Brown JP, 2012, ENERG ECON, V34, P1743, DOI 10.1016/j.eneco.2012.07.010.
   Burrows L. R, 2013, P BIENN C EC SOC S A, P1.
   Cambridge Econometrics, 2017, FUT UK EMPL OFFSH WI.
   Croatian Bureau of Statistics, INP OUTP TABL 2010.
   De Carvalho Bras T. M., 2014, THESIS.
   Deloitte, 2012, MACR IMP WIND EN SEC.
   Ejdemo T, 2015, RENEW SUST ENERG REV, V47, P476, DOI 10.1016/j.rser.2015.03.082.
   Garrett-Peltier H, 2017, ECON MODEL, V61, P439, DOI 10.1016/j.econmod.2016.11.012.
   Greene JS, 2013, ENERGY SUSTAIN SOC, V3, DOI 10.1186/2192-0567-3-2.
   Haerer D, 2015, ENERG POLICY, V82, P85, DOI 10.1016/j.enpol.2015.03.006.
   Hrvatska Energetska Regulatorna Agencija (Croatian Energy Regulatory Agency), 2017, GOD IZVJ RAD HRVATSK.
   Hrvatski Sabor (Croatian Parliament), 2009, STRAT EN RAZV REP HR.
   Blanco MI, 2009, ENERG POLICY, V37, P2847, DOI 10.1016/j.enpol.2009.02.049.
   Jaraite J, 2017, ENERG J, V38, P197, DOI 10.5547/01956574.38.5.jjar.
   Lantz E., 2009, NRELTP50044344.
   Lehr U, 2008, ENERG POLICY, V36, P108, DOI 10.1016/j.enpol.2007.09.004.
   Markaki M, 2013, ENERG POLICY, V57, P263, DOI 10.1016/j.enpol.2013.01.047.
   McLennan W, 2006, INFORM PAPER AUSTR N.
   Mikulk D., 2018, OSNOVE INPUT OUTPUT.
   Miller R. E., 2009, INPUT OUTPUT ANAL FD.
   Ministarstvo Gospodarstva Republike Hrvatske (Ministry of Economy), 2013, NAC AKC PLAN OBN IZV.
   Oliveira C, 2014, P 22 INT INP OUTP C.
   Raa TT, 2005, ECONOMICS OF INPUT-OUTPUT ANALYSIS, P1, DOI 10.2277/ 052160267X.
   Ragwitz M., 2009, TREND14742006 EUR CO.
   Simas M, 2014, RENEW SUST ENERG REV, V31, P83, DOI 10.1016/j.rser.2013.11.046.
   Slattery MC, 2011, ENERG POLICY, V39, P7930, DOI 10.1016/j.enpol.2011.09.047.
   Soukissian TH, 2017, ENERGIES, V10, DOI 10.3390/en10101512.
   {*}UN, 1996, HDB INP OUTP TABL CO.
   Vagiona DG, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10030749.
   Varela-Vazquez P, 2017, RENEW ENERG, V111, P815, DOI 10.1016/j.renene.2017.05.002.
   Xia F, 2017, ENERG POLICY, V110, P263, DOI 10.1016/j.enpol.2017.08.030.
   Zikovic S, 2015, MEDUNAR ZNAN SIMP GO, P537.}},
Number-of-Cited-References = {{34}},
Times-Cited = {{4}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{4}},
Journal-ISO = {{Energies}},
Doc-Delivery-Number = {{GQ6MQ}},
Unique-ID = {{ISI:000441830500265}},
OA = {{DOAJ Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000441277800007,
Author = {Zhao, Shaohua and Liu, Zhifei and Colin, Christophe and Zhao, Yulong and
   Wang, Xingxing and Jian, Zhimin},
Title = {{Responses of the East Asian Summer Monsoon in the Low-Latitude South
   China Sea to High-Latitude Millennial-Scale Climatic Changes During the
   Last Glaciation: Evidence From a High-Resolution Clay Mineralogical
   Record}},
Journal = {{PALEOCEANOGRAPHY AND PALEOCLIMATOLOGY}},
Year = {{2018}},
Volume = {{33}},
Number = {{7}},
Pages = {{745-765}},
Month = {{JUL}},
Abstract = {{High-resolution clay mineral assemblage combined with Nd and Sr isotopic
   compositions of Core MD12-3434 located in the northern South China Sea
   was investigated to reveal terrigenous sediment response to the East
   Asian monsoon evolution during the last glaciation. Clay mineralogical
   variations indicate clear millennial-scale oscillations that are mainly
   due to rapid changes in the proportion of smectite to illite and
   chlorite. Smectite is derived predominantly from rapid chemical
   weathering of volcanic rocks in Luzon under strong summer monsoon, while
   illite and chlorite are mainly sourced from Taiwan through reinforced
   physical erosion. Thus, the smectite/(illite+chlorite) ratio is adopted
   to reconstruct the East Asian summer monsoon evolution during the last
   glaciation. Rapid increases in the smectite/(illite+chlorite) ratio
   imply strengthened summer monsoon occurred during Dansgaard-Oeschger and
   Bolling-Allerod interstadials. In contrast, rapid decreases in the ratio
   indicate relatively weakened summer monsoon happened during Heinrich and
   Younger Dryas stadials. These millennial-scale climatic signals
   documented by clay mineralogical compositions of deep-sea sediments in
   the South China Sea can be better preserved in calm deeper-water
   sedimentary environments. Our study highlights the prompt responses of
   the East Asian monsoon system to millennial-scale climatic changes
   occurred in high-latitude Northern Hemisphere through contemporaneous
   chemical weathering of volcanic rocks and/or sediment supply variations
   under strong physical erosion in the low-latitude South China Sea,
   implying an atmospheric teleconnection from the North Atlantic to the
   Asian monsoon region.
   Plain Language Summary This study presents the first deep-sea
   high-resolution clay mineralogical result to show the low-latitude East
   Asian monsoon system that actually responds to millennial-scale changes
   in high-latitude Northern Hemisphere. The mechanism is clay minerals as
   chemical weathering products on the Earth's surface to be
   contemporaneously affected from the global and regional climate changes.
   This study also indicates that millennial-scale climatic signals
   documented by clay minerals can be better preserved in deep and calm
   sedimentary environments to avoid interruptions of potential deep-sea
   sedimentary dynamic processes like contour currents.}},
Publisher = {{AMER GEOPHYSICAL UNION}},
Address = {{2000 FLORIDA AVE NW, WASHINGTON, DC 20009 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Liu, ZF (Corresponding Author), Tongji Univ, State Key Lab Marine Geol, Shanghai, Peoples R China.
   Zhao, Shaohua; Liu, Zhifei; Zhao, Yulong; Wang, Xingxing; Jian, Zhimin, Tongji Univ, State Key Lab Marine Geol, Shanghai, Peoples R China.
   Colin, Christophe, Univ Paris Sud, UMR CNRS 8148, Lab Geosci Paris Sud, Orsay, France.}},
DOI = {{10.1029/2017PA003235}},
ISSN = {{2572-4517}},
EISSN = {{2572-4525}},
Keywords = {{clay mineralogy; millennial-scale climatic change; last glaciation; East
   Asian summer monsoon; South China Sea}},
Keywords-Plus = {{DEEP-WATER CIRCULATION; NORTH-ATLANTIC; GEOCHEMICAL INVESTIGATIONS;
   HOLOCENE EVOLUTION; TROPICAL ATLANTIC; FLUVIAL SEDIMENTS; EROSION
   PATTERNS; LATE PLEISTOCENE; ORBITAL-SCALE; OCEAN}},
Research-Areas = {{Geology; Oceanography; Paleontology}},
Web-of-Science-Categories  = {{Geosciences, Multidisciplinary; Oceanography; Paleontology}},
Author-Email = {{lzhifei@tongji.edu.cn}},
ResearcherID-Numbers = {{Liu, Zhifei/L-8817-2019
   }},
ORCID-Numbers = {{Colin, Christophe/0000-0002-3934-5191
   Zhao, Yulong/0000-0003-4298-4469}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}91528304, 41530964]; State Oceanic Administration
   of China {[}GASI-GEOGE-04]}},
Funding-Text = {{We would like to thank the captain, officers, and crew of R/V Marion
   Dufresne for their cooperation in collecting sediment cores during the
   CIRCEA cruise in 2012. Gert J. de Lange (Utrecht University) is
   appreciated for his constructive comments that help to improve this
   paper. The work is financially supported by the National Natural Science
   Foundation of China (91528304 and 41530964) and the State Oceanic
   Administration of China (GASI-GEOGE-04). The study is a part of the
   French-Chinese collaborative project of International Associated
   Laboratories (LIA) MONOCL. The clay mineralogical data used in this
   paper can be found in the supporting information.}},
Cited-References = {{Ali S, 2015, GEOCHEM GEOPHY GEOSY, V16, P505, DOI 10.1002/2014GC005586.
   Andersen KK, 2004, NATURE, V431, P147, DOI 10.1038/nature02805.
   Beaulieu E, 2012, NAT CLIM CHANGE, V2, P346, DOI {[}10.1038/nclimate1419, 10.1038/NCLIMATE1419].
   BERGER AL, 1978, J ATMOS SCI, V35, P2362, DOI 10.1175/1520-0469(1978)035<2362:LTVODI>2.0.CO;2.
   BISCAYE PE, 1965, GEOL SOC AM BULL, V76, P803, DOI 10.1130/0016-7606(1965)76{[}803:MASORD]2.0.CO;2.
   Black DE, 2009, EARTH PLANET SC LETT, V279, P139, DOI 10.1016/j.epsl.2008.12.040.
   Blunier T, 1998, NATURE, V394, P739, DOI 10.1038/29447.
   BOND G, 1993, NATURE, V365, P143, DOI 10.1038/365143a0.
   Boulay S, 2005, PALAEOGEOGR PALAEOCL, V228, P260, DOI 10.1016/j.palaeo.2005.06.005.
   Chang YP, 2009, PALEOCEANOGRAPHY, V24, DOI 10.1029/2007PA001577.
   Chen Q, 2017, SCI REP-UK, V7, DOI 10.1038/srep42083.
   Cheng H, 2016, NATURE, V534, P640, DOI 10.1038/nature18591.
   Clift PD, 2014, EARTH-SCI REV, V130, P86, DOI 10.1016/j.earscirev.2014.01.002.
   Colin C, 2014, PALAEOGEOGR PALAEOCL, V401, P81, DOI 10.1016/j.palaeo.2014.02.015.
   Copard K, 2010, QUATERNARY SCI REV, V29, P2499, DOI 10.1016/j.quascirev.2010.05.025.
   Dadson SJ, 2003, NATURE, V426, P648, DOI 10.1038/nature02150.
   DANSGAARD W, 1993, NATURE, V364, P218, DOI 10.1038/364218a0.
   Deplazes G, 2013, NAT GEOSCI, V6, P213, DOI 10.1038/ngeo1712.
   Ding XD, 2016, PALAEOGEOGR PALAEOCL, V450, P38, DOI 10.1016/j.palaeo.2016.02.048.
   Dosseto A, 2015, GEOCHEM PERSPECT LET, V1, P10, DOI 10.7185/geochemlet.1502.
   Dykoski CA, 2005, EARTH PLANET SC LETT, V233, P71, DOI 10.1016/j.epsl.2005.01.036.
   Fang G. H., 1998, ACTA OCEANOGR TAIWAN, V37, P1.
   Gislason SR, 2009, EARTH PLANET SC LETT, V277, P213, DOI 10.1016/j.epsl.2008.10.018.
   Grinsted A, 2004, NONLINEAR PROC GEOPH, V11, P561, DOI 10.5194/npg-11-561-2004.
   Guo Z, 1996, CLIM DYNAM, V12, P701, DOI 10.1007/s003820050137.
   Hartshorn K, 2002, SCIENCE, V297, P2036, DOI 10.1126/science.1075078.
   HEINRICH H, 1988, QUATERNARY RES, V29, P142, DOI 10.1016/0033-5894(88)90057-9.
   Henry LG, 2016, SCIENCE, V353, P470, DOI 10.1126/science.aaf5529.
   Holtzapffel T, 1985, SOC GEOL NORD PUBL, V12, P1.
   Hsin YC, 2012, J GEOPHYS RES-OCEANS, V117, DOI 10.1029/2011JC007714.
   Hu DK, 2013, GEOCHEM GEOPHY GEOSY, V14, P2349, DOI 10.1002/ggge.20166.
   Hu J. Y., 2000, J OCEANOGR, V56, P607, DOI DOI 10.1023/A:1011117531252.
   Huang J, 2011, QUATERNARY RES, V75, P734, DOI 10.1016/j.yqres.2011.03.002.
   JACOBSEN SB, 1980, EARTH PLANET SC LETT, V50, P139, DOI 10.1016/0012-821X(80)90125-9.
   Jiang H, 2006, J QUATERNARY SCI, V21, P377, DOI 10.1002/jqs.1000.
   Kissel C., 2012, RAPPORTS CAMPAGNE ME.
   Li N, 2019, J ASIAN EARTH SCI, V171, P78, DOI 10.1016/j.jseaes.2017.06.005.
   Lin DC, 2006, PALAEOGEOGR PALAEOCL, V236, P56, DOI 10.1016/j.palaeo.2005.11.039.
   Lin DC, 2014, QUATERN INT, V333, P207, DOI 10.1016/j.quaint.2014.03.062.
   Liu JG, 2014, GEOCHEM GEOPHY GEOSY, V15, P2727, DOI 10.1002/2013GC005202.
   Liu ZF, 2004, MAR GEOL, V209, P1, DOI 10.1016/j.margeo.2004.06.004.
   Liu ZF, 2003, MAR GEOL, V201, P133, DOI 10.1016/S0025-3227(03)00213-5.
   Liu ZF, 2007, GEOCHEM GEOPHY GEOSY, V8, DOI 10.1029/2006GC001490.
   Liu ZF, 2016, EARTH-SCI REV, V153, P238, DOI 10.1016/j.earscirev.2015.08.005.
   Liu ZF, 2014, J ASIAN EARTH SCI, V79, P507, DOI 10.1016/j.jseaes.2013.11.003.
   Liu ZF, 2010, CHINESE SCI BULL, V55, P4058, DOI 10.1007/s11434-010-4149-5.
   Liu ZF, 2010, MAR GEOL, V277, P48, DOI 10.1016/j.margeo.2010.08.010.
   Liu ZF, 2009, APPL GEOCHEM, V24, P2195, DOI 10.1016/j.apgeochem.2009.09.025.
   Liu ZF, 2008, MAR GEOL, V255, P149, DOI 10.1016/j.margeo.2008.08.003.
   Markle BR, 2017, NAT GEOSCI, V10, P36, DOI {[}10.1038/NGEO2848, 10.1038/ngeo2848].
   McManus JF, 2004, NATURE, V428, P834, DOI 10.1038/nature02494.
   Nagashima K, 2007, PALAEOGEOGR PALAEOCL, V247, P144, DOI 10.1016/j.palaeo.2006.11.027.
   Nagashima K, 2011, J ASIAN EARTH SCI, V40, P1214, DOI 10.1016/j.jseaes.2010.08.010.
   Oppo DW, 2005, GEOLOGY, V33, P785, DOI 10.1130/G21867.1.
   Partin JW, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms9061.
   Peterson LC, 2000, SCIENCE, V290, P1947, DOI 10.1126/science.290.5498.1947.
   Petschick R, 2000, MACDIFF 4 2 2.
   PORTER SC, 1995, NATURE, V375, P305, DOI 10.1038/375305a0.
   Reimer PJ, 2013, RADIOCARBON, V55, P1869, DOI 10.2458/azu\_js\_rc.55.16947.
   Riboulleau A, 2014, QUATERNARY SCI REV, V94, P62, DOI 10.1016/j.quascirev.2014.04.023.
   Sabatier P, 2010, SEDIMENT GEOL, V228, P205, DOI 10.1016/j.sedgeo.2010.04.012.
   Sawada K, 1998, NATURE, V392, P592, DOI 10.1038/33391.
   Schmidt MW, 2012, P NATL ACAD SCI USA, V109, P14348, DOI 10.1073/pnas.1207806109.
   Schneider T, 2014, NATURE, V513, P45, DOI 10.1038/nature13636.
   Schopka HH, 2011, GEOCHIM COSMOCHIM AC, V75, P978, DOI 10.1016/j.gca.2010.11.014.
   Schroeder A, 2015, EARTH PLANET SC LETT, V430, P30, DOI 10.1016/j.epsl.2015.08.001.
   Selvaraj K, 2006, J GEOL, V114, P101, DOI 10.1086/498102.
   Sun YB, 2012, NAT GEOSCI, V5, P46, DOI {[}10.1038/ngeo1326, 10.1038/NGEO1326].
   Tada R, 2004, GEOPHYS MONOGR SER, V149, P283, DOI 10.1029/149GM15.
   Tada R, 1999, PALEOCEANOGRAPHY, V14, P236, DOI 10.1029/1998PA900016.
   Tjallingii R, 2008, NAT GEOSCI, V1, P670, DOI 10.1038/ngeo289.
   Wan SM, 2007, PALAEOGEOGR PALAEOCL, V254, P561, DOI 10.1016/j.palaeo.2007.07.009.
   Wang B, 2008, J CLIMATE, V21, P4449, DOI 10.1175/2008JCLI2183.1.
   Wang L, 1999, MAR GEOL, V156, P245, DOI 10.1016/S0025-3227(98)00182-0.
   Wang LJ, 1990, PALEOCEANOGRAPHY, V5, P77, DOI 10.1029/PA005i001p00077.
   Wang PX, 2014, CLIM PAST, V10, P2007, DOI 10.5194/cp-10-2007-2014.
   Wang PX, 2017, EARTH-SCI REV, V174, P84, DOI 10.1016/j.earscirev.2017.07.006.
   Wang PX, 2014, MAR GEOL, V352, P381, DOI 10.1016/j.margeo.2014.03.003.
   Wang X., 2015, THESIS.
   Wang YJ, 2001, SCIENCE, V294, P2345, DOI 10.1126/science.1064618.
   Wang YJ, 2008, NATURE, V451, P1090, DOI 10.1038/nature06692.
   Wei GJ, 2007, PALAEOGEOGR PALAEOCL, V250, P126, DOI 10.1016/j.palaeo.2007.03.005.
   Wen XY, 2016, NAT COMMUN, V7, DOI 10.1038/ncomms11999.
   Wu CR, 2017, SCI REP-UK, V7, DOI 10.1038/s41598-017-08206-4.
   Wu CR, 2013, PROG OCEANOGR, V110, P49, DOI 10.1016/j.pocean.2012.12.001.
   Wu CR, 2012, J GEOPHYS RES-OCEANS, V117, DOI 10.1029/2012JC007968.
   Xie X, 2014, CHINESE SCI BULL, V59, P776, DOI 10.1007/s11434-014-0117-9.
   Yu ZJ, 2016, EARTH PLANET SC LETT, V446, P45, DOI 10.1016/j.epsl.2016.04.022.
   Zhao MX, 2006, PALAEOGEOGR PALAEOCL, V236, P39, DOI 10.1016/j.palaeo.2005.11.033.
   Zhao SH, 2017, SCI CHINA EARTH SCI, V60, P1368, DOI 10.1007/s11430-016-9058-6.
   Zhao W, 2014, J GEOPHYS RES-OCEANS, V119, P790, DOI 10.1002/2013JC009587.
   Zhao YL, 2015, EARTH PLANET SC LETT, V430, P477, DOI 10.1016/j.epsl.2015.09.008.
   Zheng XF, 2016, GEOPHYS RES LETT, V43, P8590, DOI 10.1002/2016GL070342.
   Zhong Y, 2017, CONT SHELF RES, V140, P11, DOI 10.1016/j.csr.2017.01.023.}},
Number-of-Cited-References = {{94}},
Times-Cited = {{8}},
Usage-Count-Last-180-days = {{3}},
Usage-Count-Since-2013 = {{27}},
Journal-ISO = {{Paleoceanogr. Paleoclimatology}},
Doc-Delivery-Number = {{GQ0AK}},
Unique-ID = {{ISI:000441277800007}},
DA = {{2020-08-06}},
}

@article{ ISI:000440332500061,
Author = {Anyamba, Assaf and Glennie, Erin and Small, Jennifer},
Title = {{Teleconnections and Interannual Transitions as Observed in African
   Vegetation: 2015-2017}},
Journal = {{REMOTE SENSING}},
Year = {{2018}},
Volume = {{10}},
Number = {{7}},
Month = {{JUL}},
Abstract = {{El Nino/Southern Oscillation (ENSO) teleconnections present a
   hemispheric dipole pattern in both rainfall and vegetation between
   eastern and southern Africa. We analyze precipitation and normalized
   difference vegetation index (NDVI) departures during the 2015-2017 ENSO
   cycle; with one of the strongest warm events (El Nino) on record
   followed by a short and weak cold event (La Nina). Typically, southern
   (eastern) Africa is associated with dry (wet) conditions during El Nino,
   and wet (dry) conditions during La Nina. In general, the temporal and
   spatial evolution of vegetation responses show the expected dipole
   pattern during the 2015-2016 El Nino and following 2016-2017 La Nina.
   However, in 2015-2016 the eastern African impacts were displaced to the
   west and south of the canonical pattern. Composites of seasonal
   vegetation anomalies highlight the magnitude and position of impacts.
   Further investigation through empirical orthogonal teleconnections and
   spatial correlation analysis confirms the similar, but opposite,
   teleconnection impacts in eastern and southern Africa. The diametrically
   opposed patterns have particular implications for agricultural
   production and the availability of fodder and forage, especially in the
   pastoral communities of the two regions.}},
Publisher = {{MDPI}},
Address = {{ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Anyamba, A (Corresponding Author), NASA, Goddard Earth Sci Technol \& Res, Univ Space Res Assoc, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA.
   Anyamba, Assaf, NASA, Goddard Earth Sci Technol \& Res, Univ Space Res Assoc, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA.
   Glennie, Erin; Small, Jennifer, NASA, Sci Syst \& Applicat Inc, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA.}},
DOI = {{10.3390/rs10071038}},
Article-Number = {{1038}},
ISSN = {{2072-4292}},
Keywords = {{normalized difference vegetation index (NDV)I; precipitation; El
   Nino/Southern Oscillation (ENSO); Indian Ocean Dipole (IOD);
   teleconnections; Africa}},
Keywords-Plus = {{SEA-SURFACE TEMPERATURE; NINO SOUTHERN-OSCILLATION; INDIAN-OCEAN DIPOLE;
   EL-NINO; EAST-AFRICA; RAINFALL; ENSO; AVHRR; NDVI; SENSITIVITY}},
Research-Areas = {{Remote Sensing}},
Web-of-Science-Categories  = {{Remote Sensing}},
Author-Email = {{Assaf.Anyamba@nasa.gov
   erin.n.glennie@nasa.gov}},
Funding-Acknowledgement = {{United States Department of Agriculture Foreign Agricultural Service}},
Funding-Text = {{This research is supported by the United States Department of
   Agriculture Foreign Agricultural Service in support of the Global
   Agriculture Monitoring system (ttps://glam1.gsfc.nasa.gov/).}},
Cited-References = {{Andujar E, 2017, ADV METEOROL, V2017, DOI 10.1155/2017/8434020.
   {[}Anonymous], 2016, KENYA GRAIN FEED ANN.
   Anyamba A, 1996, INT J REMOTE SENS, V17, P2533, DOI 10.1080/01431169608949091.
   Anyamba A, 2002, J CLIMATE, V15, P3096, DOI 10.1175/1520-0442(2002)015\<3096:FENOTL\>2.0.CO;2.
   Ashok K, 2003, J METEOROL SOC JPN, V81, P41, DOI 10.2151/jmsj.81.41.
   Behera SK, 2006, J CLIMATE, V19, P1688, DOI 10.1175/JCLI3797.1.
   Birkett C, 1999, GEOPHYS RES LETT, V26, P1031, DOI 10.1029/1999GL900165.
   Black E, 2005, PHILOS T R SOC A, V363, P43, DOI 10.1098/rsta.2004.1474.
   Didan K., 2015, MODIS VEGETATION IND, V3.
   Dommenget D, 2011, CLIM DYNAM, V36, P2129, DOI 10.1007/s00382-010-0787-1.
   FAOSTAT, 2017, FAO STAT DAT FOOD AG.
   Field RD, 2016, P NATL ACAD SCI USA, V113, P9204, DOI 10.1073/pnas.1524888113.
   Glennie E, 2018, INT J APPL EARTH OBS, V68, P180, DOI 10.1016/j.jag.2017.12.011.
   Huang BY, 2015, J CLIMATE, V28, P911, DOI 10.1175/JCLI-D-14-00006.1.
   Ichii K, 2002, INT J REMOTE SENS, V23, P3873, DOI 10.1080/01431160110119416.
   Jeong HI, 2017, INT J CLIMATOL, V37, P2193, DOI 10.1002/joc.4813.
   Jimenez-Munoz JC, 2016, SCI REP-UK, V6, DOI 10.1038/srep33130.
   Kao HY, 2009, J CLIMATE, V22, P615, DOI 10.1175/2008JCLI2309.1.
   Love T.B., 2004, P 84 AM MET SOC ANN, P5213.
   Martiny N, 2006, INT J REMOTE SENS, V27, P5201, DOI 10.1080/01431160600567787.
   Martiny N, 2005, GEOPHYS RES LETT, V32, DOI 10.1029/2005GL024634.
   McPhaden MJ, 2006, SCIENCE, V314, P1740, DOI 10.1126/science.1132588.
   Mladenova IE, 2017, IEEE J-STARS, V10, P1328, DOI 10.1109/JSTARS.2016.2639338.
   Myneni RB, 1996, GEOPHYS RES LETT, V23, P729, DOI 10.1029/96GL00266.
   Neelin JD, 1998, PHYS TODAY, V51, P32.
   Nicholson SE, 1997, INT J CLIMATOL, V17, P117, DOI 10.1002/(SICI)1097-0088(199702)17:2<117::AID-JOC84>3.0.CO;2-O.
   NICHOLSON SE, 1990, CLIMATIC CHANGE, V17, P209, DOI 10.1007/BF00138369.
   Novella NS, 2016, J APPL METEOROL CLIM, V55, P2575, DOI 10.1175/JAMC-D-16-0111.1.
   Parhi P, 2016, J CLIMATE, V29, P1461, DOI 10.1175/JCLI-D-15-0071.1.
   Philippon N, 2014, J CLIMATE, V27, P2509, DOI 10.1175/JCLI-D-13-00365.1.
   Pinzon JE, 2014, REMOTE SENS-BASEL, V6, P6929, DOI 10.3390/rs6086929.
   RASMUSSON EM, 1982, MON WEATHER REV, V110, P354, DOI 10.1175/1520-0493(1982)110<0354:VITSST>2.0.CO;2.
   Rasmusson EM, 1990, J MARINE SYST, V1, P71, DOI 10.1016/0924-7963(90)90153-2.
   Richard Y, 1998, INT J REMOTE SENS, V19, P2907, DOI 10.1080/014311698214343.
   ROPELEWSKI CF, 1987, MON WEATHER REV, V115, P1606, DOI 10.1175/1520-0493(1987)115<1606:GARSPP>2.0.CO;2.
   Saji NH, 1999, NATURE, V401, P360, DOI 10.1038/43855.
   Singleton AT, 2006, TELLUS A, V58, P355, DOI 10.1111/j.1600-0870.2006.00180.x.
   Stige LC, 2006, P NATL ACAD SCI USA, V103, P3049, DOI 10.1073/pnas.0600057103.
   Takahashi K, 2011, GEOPHYS RES LETT, V38, DOI 10.1029/2011GL047364.
   Trenberth KE, 1997, B AM METEOROL SOC, V78, P2771, DOI 10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2.
   van den Dool HM, 2000, J CLIMATE, V13, P1421, DOI 10.1175/1520-0442(2000)013<1421:EOT>2.0.CO;2.
   Webster PJ, 1999, NATURE, V401, P356, DOI 10.1038/43848.
   Williams CA, 2011, BIOGEOSCIENCES, V8, P27, DOI 10.5194/bg-8-27-2011.
   Yamagata T, 2003, B AM METEOROL SOC, V84, P1418, DOI 10.1175/BAMS-84-10-1418.
   Yeh SW, 2014, ASIA-PAC J ATMOS SCI, V50, P69, DOI 10.1007/s13143-014-0028-3.
   Zhang XY, 2016, ISPRS J PHOTOGRAMM, V114, P191, DOI 10.1016/j.isprsjprs.2016.02.010.
   Zhao YJ, 2015, J CLIMATE, V28, P3, DOI 10.1175/JCLI-D-14-00047.1.}},
Number-of-Cited-References = {{47}},
Times-Cited = {{5}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{5}},
Journal-ISO = {{Remote Sens.}},
Doc-Delivery-Number = {{GO8IV}},
Unique-ID = {{ISI:000440332500061}},
OA = {{DOAJ Gold}},
DA = {{2020-08-06}},
}

@article{ ISI:000439794000002,
Author = {Cheng, Zhigang and Qiao, Yunting and Jian, Maoqiu and Siems, Steven T.},
Title = {{Inter-decadal change of leading pattern of spring rainfall over southern
   China during 1901-2010}},
Journal = {{INTERNATIONAL JOURNAL OF CLIMATOLOGY}},
Year = {{2018}},
Volume = {{38}},
Number = {{9}},
Pages = {{3494-3512}},
Month = {{JUL}},
Abstract = {{Spring rainfall over southern China experiences both strong inter-annual
   variability and inter-decadal variability. Employing the monthly
   precipitation data from 1901 to 2010, this research examines the
   inter-decadal change of the leading pattern of spring rainfall over
   southern China. Based on the empirical orthogonal function (EOF)
   analysis, four distinctive precipitation periods (epochs) have been
   identified: 1901-1937, 1938-1958, 1959-1994 and 1995-2010. During the
   first and third epochs, the centre of the inter-annual variation of
   spring rainfall is located in the South China (SC) region. Low-latitude
   climate forcing plays an important role in the inter-annual variation of
   the spring rainfall anomaly over the SC region within these epochs.
   During typical eastern Pacific El Nino conditions, the western Pacific
   subtropical high (WPSH) is stronger, driving an abnormally warm, moist
   southeasterly air mass across the South China Sea and onto the SC
   region. In addition, an anomalous vertical circulation is forced with
   ascent over the warmer eastern Pacific, descent over the cooler western
   Pacific and ascent again over the SC region. During the second and
   fourth epochs, the maximum of the leading mode of the spring
   precipitation anomaly is located in the mid-lower reaches of the Yangtze
   River (MLRYR) region. Counter to the first and third epochs, the leading
   mode of the spring rainfall anomaly is mainly attributed to mid- and
   high-latitude forcing during the second epoch. In the wet years a
   negative Eurasian teleconnection (EU) wave train is observed with a
   positive anomaly in 500hPa geopotential height located over southern
   Japan. The WPSH is located further to the north, bringing more water
   vapour into the MLRYR region from the northwestern Pacific. During the
   fourth epoch, the EU wave train and WPSH are similar to those of the
   second epoch. Furthermore, a central Pacific El Nino pattern is evident
   in the wet years, suggesting a wider teleconnection.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Qiao, YT (Corresponding Author), Sun Yat Sen Univ, Sch Atmospher Sci, 135 West Xingang Rd, Guangzhou 510275, Guangdong, Peoples R China.
   Cheng, Zhigang; Qiao, Yunting; Jian, Maoqiu, Sun Yat Sen Univ, Guangdong Prov Key Lab Climate Change \& Nat Disas, Ctr Monsoon \& Environm Res, Sch Atmospher Sci, Guangzhou, Guangdong, Peoples R China.
   Cheng, Zhigang, CMA, Inst Urban Meteorol, Beijing, Peoples R China.
   Siems, Steven T., Monash Univ, Sch Earth Atmosphere \& Environm, Melbourne, Vic, Australia.}},
DOI = {{10.1002/joc.5511}},
ISSN = {{0899-8418}},
EISSN = {{1097-0088}},
Keywords = {{EOF analysis; mid-lower reaches of the Yangtze River; South China;
   spring rainfall; western Pacific subtropical high}},
Keywords-Plus = {{PERSISTENT RAINS; SUMMER; MECHANISM; OSCILLATION; MONSOON; IMPACTS;
   WINTER}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{qiaoyt@mail.sysu.edu.cn}},
ResearcherID-Numbers = {{Siems, Steven T/C-8339-2013}},
ORCID-Numbers = {{Siems, Steven T/0000-0002-8478-533X}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}41575069]; National Key Research Program of China
   {[}2014CB953901]; National Key Research and Development Program of China
   {[}2016YFA0600601]; China Scholarship CouncilChina Scholarship Council;
   Jiangsu Collaborative Innovation Center for Climate Change}},
Funding-Text = {{National Natural Science Foundation of China, Grant/Award Number:
   41575069; National Key Research Program of China, Grant/Award Number:
   2014CB953901; National Key Research and Development Program of China,
   Grant/Award Number: 2016YFA0600601; China Scholarship Council; Jiangsu
   Collaborative Innovation Center for Climate Change}},
Cited-References = {{Ashok K, 2007, J GEOPHYS RES-OCEANS, V112, DOI 10.1029/2006JC003798.
   Bai XX, 2013, J TROP METEOROL, V19, P214.
   Cai Jiaxi, 2011, Acta Meteorologica Sinica, V69, P99.
   Chen D., 2012, J CHENGDU U INFO TEC, V27, P479.
   Chen JP, 2014, PARASITOL RES MG, V6, P43, DOI 10.1007/978-3-642-39824-7\_4.
   {[}陈绍东 Chen Shaodong], 2003, {[}热带气象学报, Journal of Tropical Meteorology], V19, P260.
   Compo GP, 2011, Q J ROY METEOR SOC, V137, P1, DOI 10.1002/qj.776.
   Feng J, 2011, J GEOPHYS RES-ATMOS, V116, DOI 10.1029/2010JD015160.
   Feng J, 2011, INT J CLIMATOL, V31, P2091, DOI 10.1002/joc.2217.
   {[}甘晶晶 Gan Jingjing], 2013, {[}气象学报, Acta Meteorologica Sinica], V71, P250.
   Herceg-Bulic I, 2014, J CLIMATE, V27, P186, DOI 10.1175/JCLI-D-12-00273.1.
   Kao HY, 2009, J CLIMATE, V22, P615, DOI 10.1175/2008JCLI2309.1.
   Lee EJ, 2005, J CLIMATE, V18, P4381, DOI 10.1175/JCLI3545.1.
   Lin ZD, 2005, ADV ATMOS SCI, V22, P199.
   Linho LH, 2008, J CLIMATE, V21, P3081, DOI 10.1175/2007JCLI1611.1.
   {[}刘宣飞 Liu Xuanfei], 2013, {[}热带气象学报, Journal of Tropical Meteorology], V29, P99.
   Pan WJ, 2013, J CLIMATE, V26, P5072, DOI 10.1175/JCLI-D-12-00618.1.
   Rayner NA, 2003, J GEOPHYS RES-ATMOS, V108, DOI 10.1029/2002JD002670.
   Schneider U., 2011, GPCC FULL DATA REANA, DOI {[}10.5676/DWD\_GPCC/FD\_M\_V6\_050, DOI 10.5676/DWD\_GPCC/FD\_M\_V6\_050, 0.5676/ DWD\_GPCC/FD\_ M\_V6\_050].
   Sun B, 2015, CLIM DYNAM, V44, P2703, DOI 10.1007/s00382-014-2251-0.
   {[}孙林海 Sun Linhai], 2004, {[}气象学报, Acta Meteorologica Sinica], V62, P355.
   Takaya K, 2001, J ATMOS SCI, V58, P608, DOI 10.1175/1520-0469(2001)058<0608:AFOAPI>2.0.CO;2.
   Tian SF, 1998, J METEOROL SOC JPN, V76, P57, DOI 10.2151/jmsj1965.76.1\_57.
   WALLACE JM, 1981, MON WEATHER REV, V109, P784, DOI 10.1175/1520-0493(1981)109<0784:TITGHF>2.0.CO;2.
   Wan RJ,