text:
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Number-of-Cited-References = {{66}},
Times-Cited = {{15}},
Usage-Count-Last-180-days = {{13}},
Usage-Count-Since-2013 = {{67}},
Journal-ISO = {{Appl. Energy}},
Doc-Delivery-Number = {{FW1QX}},
Unique-ID = {{ISI:000425075600006}},
DA = {{2020-08-06}},
}

@article{ ISI:000425075600045,
Author = {Zhang, Zengkai and Lin, Jintai},
Title = {{From production-based to consumption-based regional carbon inventories:
   Insight from spatial production fragmentation}},
Journal = {{APPLIED ENERGY}},
Year = {{2018}},
Volume = {{211}},
Pages = {{549-567}},
Month = {{FEB 1}},
Abstract = {{The key distinction between production-based and consumption-based
   accounting lies in the way in which trade embodied emissions are
   allocated between producer and consumer regions. Yet, these two regions
   are not necessarily directly connected to each other in supply chains,
   due to spatial production fragmentation. To better understand the link
   from the production-based to the consumption-based regional carbon
   inventories, this paper defines the economic length of carbon transfer
   (ELCT) as the number of administrative border-crossing involved in the
   influence process of a region's final demand on the carbon emissions of
   another region. Using a multi regional input-output analysis framework
   for China, we propose an approach to calculating the ELCT related to a
   region's production or demand for domestic consumption or international
   export. We find that the average ELCT in 2010 is 1.34 and that more than
   a quarter of interregional carbon transfer crosses provincial borders
   twice or more. The provincial and sectoral analysis of ELCT reveals that
   spatial production fragmentation is an important challenge to be
   conquered for successful implementation of consumption-based climate
   regulations.}},
Publisher = {{ELSEVIER SCI LTD}},
Address = {{THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Zhang, ZK (Corresponding Author), Tianjin Univ, Coll Management \& Econ, Tianjin 300072, Peoples R China.
   Zhang, Zengkai, Tianjin Univ, Coll Management \& Econ, Tianjin 300072, Peoples R China.
   Zhang, Zengkai, Nankai Univ, China Reg Econ Applicat Lab, Tianjin 300071, Peoples R China.
   Lin, Jintai, Peking Univ, Sch Phys, Dept Atmospher \& Ocean Sci, Lab Climate \& Ocean Atmosphere Studies, Beijing 100871, Peoples R China.}},
DOI = {{10.1016/j.apenergy.2017.11.047}},
ISSN = {{0306-2619}},
EISSN = {{1872-9118}},
Keywords = {{Carbon accounting; Carbon transfer; Spatial production fragmentation;
   Border-crossing frequency; Input-output model}},
Keywords-Plus = {{INPUT-OUTPUT-ANALYSIS; INTERNATIONAL-TRADE; CO2 EMISSIONS;
   AIR-POLLUTION; SUPPLY CHAINS; TRANSFERS; GROWTH; RESPONSIBILITY;
   FOOTPRINT; POLICY}},
Research-Areas = {{Energy \& Fuels; Engineering}},
Web-of-Science-Categories  = {{Energy \& Fuels; Engineering, Chemical}},
Author-Email = {{zengkaizhang@tju.edu.cn}},
ResearcherID-Numbers = {{Lin, Jintai/A-8872-2012}},
ORCID-Numbers = {{Lin, Jintai/0000-0002-2362-2940}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71603179, 41422502]; Tianjin Program of
   Philosophy and Social Science {[}TJGL16-007Q]; Seed Foundation of
   Tianjin University {[}2017XSZ-0016]}},
Funding-Text = {{The authors are grateful for comments and suggestions from Geoffrey J.
   D. Hewings and gratefully acknowledge the financial support from the
   National Natural Science Foundation of China (71603179 and 41422502),
   Tianjin Program of Philosophy and Social Science (TJGL16-007Q), and Seed
   Foundation of Tianjin University (2017XSZ-0016). We also would like to
   thank the anonymous referees and the editors.}},
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Number-of-Cited-References = {{72}},
Times-Cited = {{10}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{38}},
Journal-ISO = {{Appl. Energy}},
Doc-Delivery-Number = {{FW1QX}},
Unique-ID = {{ISI:000425075600045}},
DA = {{2020-08-06}},
}

@article{ ISI:000425328700022,
Author = {Hua, Wenjian and Zhou, Liming and Chen, Haishan and Nicholson, Sharon E.
   and Jiang, Yan and Raghavendra, Ajay},
Title = {{Understanding the Central Equatorial African long-term drought using
   AMIP-type simulations}},
Journal = {{CLIMATE DYNAMICS}},
Year = {{2018}},
Volume = {{50}},
Number = {{3-4}},
Pages = {{1115-1128}},
Month = {{FEB}},
Abstract = {{Previous studies show that Indo-Pacific sea surface temperature (SST)
   variations may help to explain the observed long-term drought during
   April-May-June (AMJ) since the 1990s over Central equatorial Africa
   (CEA). However, the underlying physical mechanisms for this drought are
   still not clear due to observation limitations. Here we use the
   AMIP-type simulations with 24 ensemble members forced by observed SSTs
   from the ECHAM4.5 model to explore the likely physical processes that
   determine the rainfall variations over CEA. We not only examine the
   ensemble mean (EM), but also compare the ``good{''} and ``poor{''}
   ensemble members to understand the intra-ensemble variability. In
   general, EM and the ``good{''} ensemble member can simulate the drought
   and associated reduced vertical velocity and anomalous anti-cyclonic
   circulation in the lower troposphere. However, the ``poor{''} ensemble
   members cannot simulate the drought and associated circulation patterns.
   These contrasts indicate that the drought is tightly associated with the
   tropical Walker circulation and atmospheric teleconnection patterns. If
   the observational circulation patterns cannot be reproduced, the CEA
   drought will not be captured. Despite the large intra-ensemble spread,
   the model simulations indicate an essential role of SST forcing in
   causing the drought. These results suggest that the long-term drought
   may result from tropical Indo-Pacific SST variations associated with the
   enhanced and westward extended tropical Walker circulation.}},
Publisher = {{SPRINGER}},
Address = {{ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Hua, WJ (Corresponding Author), SUNY Albany, Dept Atmospher \& Environm Sci, Albany, NY 12222 USA.
   Hua, WJ (Corresponding Author), Nanjing Univ Informat Sci \& Technol, Key Lab Meteorol Disaster, Joint Int Res Lab Climate \& Environm Change ILCEC, Minist Educ KLME,CICFEMD, Nanjing 210044, Jiangsu, Peoples R China.
   Hua, Wenjian; Zhou, Liming; Jiang, Yan; Raghavendra, Ajay, SUNY Albany, Dept Atmospher \& Environm Sci, Albany, NY 12222 USA.
   Hua, Wenjian; Chen, Haishan, Nanjing Univ Informat Sci \& Technol, Key Lab Meteorol Disaster, Joint Int Res Lab Climate \& Environm Change ILCEC, Minist Educ KLME,CICFEMD, Nanjing 210044, Jiangsu, Peoples R China.
   Nicholson, Sharon E., Florida State Univ, Earth Ocean \& Atmospher Sci, Tallahassee, FL 32306 USA.}},
DOI = {{10.1007/s00382-017-3665-2}},
ISSN = {{0930-7575}},
EISSN = {{1432-0894}},
Keywords = {{Central Equatorial Africa; Drought; AMIP; Sea surface temperature}},
Keywords-Plus = {{SEA-SURFACE TEMPERATURE; RAINFALL VARIABILITY; GENERAL-CIRCULATION;
   WALKER CIRCULATION; SAHEL DROUGHT; LAND-USE; CLIMATE; PRECIPITATION;
   ENSEMBLE; DYNAMICS}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{whua@albany.edu}},
ResearcherID-Numbers = {{Raghavendra, Ajay/Q-9322-2019
   Zhou, Liming/A-2688-2012
   Hua, Wenjian/Y-2834-2018
   Chen, Haishan/W-3747-2018
   }},
ORCID-Numbers = {{Zhou, Liming/0000-0002-7009-2487
   Hua, Wenjian/0000-0002-9705-3234
   Chen, Haishan/0000-0002-2403-3187
   Raghavendra, Ajay/0000-0002-1707-6963}},
Funding-Acknowledgement = {{National Science FoundationNational Science Foundation (NSF) {[}NSF
   AGS-1535426, AGS-1535439]; National Natural Science Foundation of
   ChinaNational Natural Science Foundation of China {[}41605034]; National
   Natural Science Foundation of Jiangsu ProvinceNatural Science Foundation
   of Jiangsu Province {[}BK20160948]; Natural Science Foundation for
   Higher Education Institutions in Jiangsu Province {[}16KJB170007];
   Priority Academic Program Development of Jiangsu Higher Education
   Institutions (PAPD)}},
Funding-Text = {{We acknowledge the International Research Institute for Climate and
   Society (IRI) working group on modeling, and we thank the modeling
   groups for producing and making their model output available. This study
   was supported by National Science Foundation (NSF AGS-1535426 and
   AGS-1535439). W.H. was jointly funded by the National Natural Science
   Foundation of China (41605034), the National Natural Science Foundation
   of Jiangsu Province (BK20160948) and the Natural Science Foundation for
   Higher Education Institutions in Jiangsu Province (16KJB170007) as well
   as project supported by the Priority Academic Program Development of
   Jiangsu Higher Education Institutions (PAPD). We also thank Prof. Aiguo
   Dai (SUNY at Albany, USA) for insightful discussion.}},
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Number-of-Cited-References = {{58}},
Times-Cited = {{11}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{11}},
Journal-ISO = {{Clim. Dyn.}},
Doc-Delivery-Number = {{FW5AP}},
Unique-ID = {{ISI:000425328700022}},
DA = {{2020-08-06}},
}

@article{ ISI:000424772100003,
Author = {Barton, Gina G. and Sandercock, Brett K.},
Title = {{Long-term changes in the seasonal timing of landbird migration on the
   Pacific Flyway}},
Journal = {{CONDOR}},
Year = {{2018}},
Volume = {{120}},
Number = {{1}},
Pages = {{30-46}},
Month = {{FEB}},
Abstract = {{The seasonal phenology of latitudinal movements is one of the key
   life-history traits of migratory birds. We used quantile regression to
   examine long-term changes in the timing of spring and autumn migration
   in 5 species of migratory passerine birds captured at a banding station
   in northern California, USA, over a 22 yr period from 1987 to 2008. Our
   5 study species included 3 short-distance migrants, Pacific-slope
   Flycatcher (Empidonax difficilis), Orange-crowned Warbler (Oreothlypis
   celata), and Wilson's Warbler (Cardellina pusilla); and 2 long-distance
   migrants, Swainson's Thrush (Catharus ustulatus) and Yellow Warbler
   (Setophaga petechia). Median timing of migration advanced in spring for
   2 of the 5 species (-2.5 days decade(-1)) but was delayed during autumn
   migration for 3 of the species (+2.9 days decade(-1)). The duration of
   the migration period also became compressed in some species but more
   protracted in others. We tested whether annual variation in migration
   timing was related to 3 indices of regional climatic conditions: the
   Pacific-North American index, multivariate El Nino-Southern Oscillation
   index, and North Atlantic Oscillation index. Climate indices explained
   relatively little of the variation in migration timing (r(2) < 0.35),
   but advances in spring migration and delays in autumn migration were
   associated with warm, wet conditions during positive phases of the
   climate indices. The strongest effects of climatic conditions on
   migration timing were found among short-distance migrants, with the
   largest changes in timing due to variation in the El Nino-Southern
   Oscillation and Pacific-North American indices. Linkages between the
   timing of movements and climatic conditions indicate that passerine
   birds on the Pacific coast exhibit phenotypic plasticity in their
   migration timing, but future studies based on experimental methods are
   needed to test alternative ecological mechanisms.}},
Publisher = {{COOPER ORNITHOLOGICAL SOC}},
Address = {{ORNITHOLOGICAL SOC NORTH AMER PO BOX 1897, LAWRENCE, KS 66044-8897 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Sandercock, BK (Corresponding Author), Kansas State Univ, Div Biol, Ackert Hall, Manhattan, KS 66506 USA.
   Sandercock, BK (Corresponding Author), Norwegian Inst Nat Res, Dept Terr Ecol, Trondheim, Norway.
   Barton, Gina G.; Sandercock, Brett K., Kansas State Univ, Div Biol, Ackert Hall, Manhattan, KS 66506 USA.
   Barton, Gina G., San Francisco Bay Bird Observ, Milpitas, CA USA.
   Sandercock, Brett K., Norwegian Inst Nat Res, Dept Terr Ecol, Trondheim, Norway.}},
DOI = {{10.1650/CONDOR-17-88.1}},
ISSN = {{0010-5422}},
EISSN = {{1938-5129}},
Keywords = {{autumn; climate indices; flycatcher; phenology; quantile regression;
   spring; thrush; timing of migration; warbler}},
Keywords-Plus = {{NORTH-ATLANTIC OSCILLATION; SPRING ARRIVAL DATES; EUROPEAN SONGBIRD
   POPULATIONS; LIGHT-LEVEL GEOLOCATORS; WOOD WARBLERS PARULIDAE; GLOBAL
   CLIMATE-CHANGE; BIRD MIGRATION; AUTUMN MIGRATION; COASTAL CALIFORNIA;
   TELECONNECTION PATTERN}},
Research-Areas = {{Zoology}},
Web-of-Science-Categories  = {{Ornithology}},
Author-Email = {{brett.sandercock@nina.no}},
ResearcherID-Numbers = {{Sandercock, Brett K/L-1644-2016}},
ORCID-Numbers = {{Sandercock, Brett K/0000-0002-9240-0268}},
Funding-Acknowledgement = {{San Francisco Bay Bird Observatory; Coyote Creek Riparian Station; Santa
   Clara Valley Water District; Pacific Gas and Electric Company; Division
   of Biology at Kansas State University}},
Funding-Text = {{Financial support for our field project was provided by individual
   members of the San Francisco Bay Bird Observatory and Coyote Creek
   Riparian Station, the Santa Clara Valley Water District, and the Pacific
   Gas and Electric Company. Financial support for the authors was provided
   by the Division of Biology at Kansas State University. None of the
   funders had input into the content of the manuscript, and none required
   approval of the manuscript before submission or publication.}},
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Number-of-Cited-References = {{102}},
Times-Cited = {{7}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{42}},
Journal-ISO = {{Condor}},
Doc-Delivery-Number = {{FV7NS}},
Unique-ID = {{ISI:000424772100003}},
OA = {{Bronze}},
DA = {{2020-08-06}},
}

@article{ ISI:000427723900029,
Author = {Semenov, V. A. and Cherenkova, E. A.},
Title = {{Evaluation of the Atlantic Multidecadal Oscillation Impact on
   Large-Scale Atmospheric Circulation in the Atlantic Region in Summer}},
Journal = {{DOKLADY EARTH SCIENCES}},
Year = {{2018}},
Volume = {{478}},
Number = {{2}},
Pages = {{263-267}},
Month = {{FEB}},
Abstract = {{The influence of the Atlantic Multidecadal Oscillation (AMO) on
   large-scale atmospheric circulation in the Atlantic region in summer for
   the period of 1950-2015 is investigated. It is shown that the
   intensification of the summer North Atlantic Oscillation (NAO) with
   significant changes in sea level pressure anomalies in the main centers
   of action (over Greenland and the British Isles) occurred while the
   North Atlantic was cooler. Sea surface temperature anomalies, which are
   linked to the AMO in the summer season, affect both the NAO index and
   fluctuations of the Eastern Atlantic/Western Russia (EAWR) centers of
   action. The positive (negative) phase of the AMO is characterized by a
   combination of negative (positive) values of the NAO and EAWR indices.
   The dominance of the opposite phases of the teleconnection indices in
   summer during the warm North Atlantic and in its colder period resulted
   in differences in the regional climate in Europe.}},
Publisher = {{MAIK NAUKA/INTERPERIODICA/SPRINGER}},
Address = {{233 SPRING ST, NEW YORK, NY 10013-1578 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Cherenkova, EA (Corresponding Author), Russian Acad Sci, Obukhov Inst Atmospher Phys, Moscow 119017, Russia.
   Cherenkova, EA (Corresponding Author), Russian Acad Sci, Inst Geog, Moscow 119017, Russia.
   Semenov, V. A.; Cherenkova, E. A., Russian Acad Sci, Obukhov Inst Atmospher Phys, Moscow 119017, Russia.
   Semenov, V. A.; Cherenkova, E. A., Russian Acad Sci, Inst Geog, Moscow 119017, Russia.}},
DOI = {{10.1134/S1028334X18020290}},
ISSN = {{1028-334X}},
EISSN = {{1531-8354}},
Keywords-Plus = {{CLIMATE; VARIABILITY}},
Research-Areas = {{Geology}},
Web-of-Science-Categories  = {{Geosciences, Multidisciplinary}},
Author-Email = {{cherenkova@igras.ru}},
ResearcherID-Numbers = {{Semenov, Vladimir/U-9488-2019
   }},
ORCID-Numbers = {{Cherenkova, Elena/0000-0002-0187-3968}},
Funding-Acknowledgement = {{Ministry of Education and Science of the Russian FederationMinistry of
   Education and Science, Russian Federation {[}14.616.21.0082]}},
Funding-Text = {{This work was supported by the Ministry of Education and Science of the
   Russian Federation (project no. 14.616.21.0082).}},
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Number-of-Cited-References = {{15}},
Times-Cited = {{2}},
Usage-Count-Last-180-days = {{0}},
Usage-Count-Since-2013 = {{14}},
Journal-ISO = {{Dokl. Earth Sci.}},
Doc-Delivery-Number = {{FZ6QJ}},
Unique-ID = {{ISI:000427723900029}},
DA = {{2020-08-06}},
}

@article{ ISI:000428829100002,
Author = {Wang, Qunwei and Hang, Ye and Su, Bin and Zhou, Peng},
Title = {{Contributions to sector-level carbon intensity change: An integrated
   decomposition analysis}},
Journal = {{ENERGY ECONOMICS}},
Year = {{2018}},
Volume = {{70}},
Pages = {{12-25}},
Month = {{FEB}},
Abstract = {{Exploring the factors driving sector-level carbon intensity change is
   important to inform targeted emission reduction policies. This paper
   proposes an integrated decomposition approach, combining
   production-theoretical decomposition analysis (PDA), index decomposition
   analysis (IDA) and attribution analysis (AA). The proposed approach can
   decompose sector-level carbon intensity change into nine driving
   factors, including two new pre-defined factors (i.e. the potential
   regional output structure effect and the output gap effect). This
   provides more detailed information about the influence of production
   technology related components, i.e. technical efficiency and
   technological change, and the contribution of each region to the
   individual driving factor. Industrial sectors across 30 provinces in
   China are used to demonstrate the integrated decomposition approach. The
   decomposition and attribution results show that the desirable output
   technological change effect is the dominant factor in decreasing
   industrial carbon intensity, of which Hebei, Shandong, Jiangsu, Liaoning
   and Henan are the main contributors. The potential energy intensity
   effect reduces industrial carbon intensity remarkably as well, mainly
   due to Henan, Liaoning, Shandong, Hunan and Inner Mongolia. Provinces
   are classifies into four performance groups based on the attribution
   results. Targeted industrial carbon intensity reduction policies should
   be implemented in different groups of provinces. (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 = {{Su, B (Corresponding Author), Natl Univ Singapore, Energy Studies Inst, 29 Heng Mui Keng Terrace, Singapore 119620, Singapore.
   Wang, Qunwei; Hang, Ye; Zhou, Peng, Nanjing Univ Aeronaut \& Astronaut, Coll Econ \& Management, 29 Jiangjun Ave, Nanjing 211106, Jiangsu, Peoples R China.
   Hang, Ye; Su, Bin, Natl Univ Singapore, Energy Studies Inst, 29 Heng Mui Keng Terrace, Singapore 119620, Singapore.}},
DOI = {{10.1016/j.eneco.2017.12.014}},
ISSN = {{0140-9883}},
EISSN = {{1873-6181}},
Keywords = {{Sector-level carbon intensity; Production-theoretical decomposition
   analysis; Index decomposition method; Attribution analysis; China}},
Keywords-Plus = {{DISTANCE FUNCTION-APPROACH; INPUT-OUTPUT-ANALYSIS;
   PRODUCTION-THEORETICAL APPROACH; DIVISIA INDEX DECOMPOSITION; CO2
   EMISSION TRENDS; ENERGY INTENSITY; DRIVING FORCES;
   ELECTRICITY-GENERATION; DIOXIDE EMISSIONS; CHINA}},
Research-Areas = {{Business \& Economics}},
Web-of-Science-Categories  = {{Economics}},
Author-Email = {{subin@nus.edu.sg}},
ResearcherID-Numbers = {{Hang, Ye/N-9815-2019
   Wang, Qunwei/AAO-4443-2020
   SU, BIN/B-7990-2011
   Zhou, Peng/A-6527-2012}},
ORCID-Numbers = {{Hang, Ye/0000-0002-1368-905X
   SU, BIN/0000-0003-4273-7054
   Zhou, Peng/0000-0003-4726-3054}},
Funding-Acknowledgement = {{National Natural Science Foundation of ChinaNational Natural Science
   Foundation of China {[}71573186]; Fundamental Research Funds for the
   Central UniversitiesFundamental Research Funds for the Central
   Universities {[}NE2017005]; Six Talents Peak Project of Jiangsu Province
   {[}JY-032]; Philosophy and Social Science Research in Colleges and
   Universities in Jiangsu Province {[}2016ZDIXM040]; Postgraduate Research
   \& Practice Innovation Program of Jiangsu Province {[}KYLX16\_0086]}},
Funding-Text = {{Authors are grateful to the financial support from the National Natural
   Science Foundation of China (no. 71573186), the Fundamental Research
   Funds for the Central Universities (no. NE2017005), Six Talents Peak
   Project of Jiangsu Province (no. JY-032), Philosophy and Social Science
   Research in Colleges and Universities in Jiangsu Province (no.
   2016ZDIXM040), and Postgraduate Research \& Practice Innovation Program
   of Jiangsu Province (no. KYLX16\_0086).}},
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Number-of-Cited-References = {{69}},
Times-Cited = {{59}},
Usage-Count-Last-180-days = {{9}},
Usage-Count-Since-2013 = {{64}},
Journal-ISO = {{Energy Econ.}},
Doc-Delivery-Number = {{GB1RY}},
Unique-ID = {{ISI:000428829100002}},
ESI-Highly-Cited-Paper = {{Y}},
ESI-Hot-Paper = {{N}},
DA = {{2020-08-06}},
}

@article{ ISI:000428829100032,
Author = {Nagashima, Fumiya},
Title = {{Critical structural paths of residential PM2.5 emissions within the
   Chinese provinces}},
Journal = {{ENERGY ECONOMICS}},
Year = {{2018}},
Volume = {{70}},
Pages = {{465-471}},
Month = {{FEB}},
Abstract = {{Consumption-based approach has provided beneficial information for
   understanding the key industries driving the huge life-cycle PM2.5
   emissions. However, the residential sector, which is the largest emitter
   of carbonaceous aerosols in China, has been treated exogenously and
   neglected in the context of consumption-based thinking. This study aims
   to extend the endogenous input-output system by incorporating
   residential PM2.5 emissions in China into the consumption -> production
   -> income process. I find that households engaged in high income
   industries such as ``other services{''}, ``agriculture{''} and
   ``construction{''} in Sichuan, Shangdong, Guangxi and Anhui mainly
   contributed their own residential PM2.5 emissions. Furthermore, the
   final demand of urban areas for construction, transport equipment and
   agriculture drove rural areas' residential emissions through production
   of commodities such as nonmetal products, coal mining, agriculture, and
   metallurgy. (C) 2018 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Nagashima, F (Corresponding Author), Kyushu Univ, Grad Sch Econ, Higashi Ku, 6-19-1 Hakozaki, Fukuoka 8128581, Japan.
   Nagashima, Fumiya, Kyushu Univ, Grad Sch Econ, Higashi Ku, 6-19-1 Hakozaki, Fukuoka 8128581, Japan.}},
DOI = {{10.1016/j.eneco.2018.01.033}},
ISSN = {{0140-9883}},
EISSN = {{1873-6181}},
Keywords = {{Multiregional input-output analysis; Residential PM2.5 emissions;
   Structural path analysis}},
Keywords-Plus = {{CONSUMPTION-BASED EMISSIONS; AIR-POLLUTION; HEALTH IMPACTS; CO2}},
Research-Areas = {{Business \& Economics}},
Web-of-Science-Categories  = {{Economics}},
Author-Email = {{3EC16105M@s.kyushu-u.ac.jp}},
ResearcherID-Numbers = {{Nagashima, Fumiya/F-8987-2018}},
ORCID-Numbers = {{Nagashima, Fumiya/0000-0001-6112-9105}},
Funding-Acknowledgement = {{JSPS Research Fellowships for Young ScientistsMinistry of Education,
   Culture, Sports, Science and Technology, Japan (MEXT)Japan Society for
   the Promotion of Science {[}17J03544]}},
Funding-Text = {{This research was supported by JSPS Research Fellowships for Young
   Scientists (No. 17J03544).}},
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Number-of-Cited-References = {{22}},
Times-Cited = {{4}},
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Journal-ISO = {{Energy Econ.}},
Doc-Delivery-Number = {{GB1RY}},
Unique-ID = {{ISI:000428829100032}},
DA = {{2020-08-06}},
}

@article{ ISI:000423816900007,
Author = {Abatan, Abayomi A. and Abiodun, Babatunde J. and Gutowski, Jr., William
   J. and Rasaq-Balogun, Saidat O.},
Title = {{Trends and variability in absolute indices of temperature extremes over
   Nigeria: linkage with NAO}},
Journal = {{INTERNATIONAL JOURNAL OF CLIMATOLOGY}},
Year = {{2018}},
Volume = {{38}},
Number = {{2}},
Pages = {{593-612}},
Month = {{FEB}},
Abstract = {{The present study examines trends in extreme temperature absolute
   indices {[}warmest day (TXx), coldest day (TXn), warmest night (TNx) and
   coldest night (TNn)] using the newly homogenized daily minimum and
   maximum temperature series from 21 stations in Nigeria for the period
   1971-2012. The indices provide an understanding of the characteristics
   of changing temperature, in light of the present anthropogenic global
   warming. Trends in the indices and the statistical significance are
   obtained using the modified Mann-Kendall test in the R-package. The
   results show that many of the stations have significant increasing
   trends in the absolute indices, with the warming most pronounced in
   Southern Nigeria. Averaged over the country, the TXx, TXn, TNx and TNn
   have absolute warming trends of 0.59, 0.17, 0.67and 0.97 degrees C,
   respectively, for the 42 years since 1971. The warming rate is highest
   during the winter (DJF) season for TNn. The present study also examines
   the possible influence of large-scale teleconnection patterns on extreme
   temperature variations by determining the correlation between the
   absolute indices and the North Atlantic Oscillation (NAO) index on
   monthly, seasonal and annual timescales. Our results show that warming
   over Nigeria during the dry season months from November to February is
   significantly correlated with NAO. The NAO has significant correlation
   with TXx and TXn in the north, and with TNx and TNn in the south. The
   analysis is repeated with ERA-20C-gridded data set, and similar
   correlations are found. The warming nights, in particular, in Nigeria
   can lead to sleeplessness and widespread mosquito-related diseases as
   the mosquito population and its parasites thrive in warmer conditions.
   The results of the analyses are relevant for decision-making process,
   especially for the development of early warning systems for extreme heat
   events.}},
Publisher = {{WILEY}},
Address = {{111 RIVER ST, HOBOKEN 07030-5774, NJ USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Abatan, AA (Corresponding Author), Iowa State Univ, Dept Geol \& Atmospher Sci, 3134 Agron Hall, Ames, IA 50011 USA.
   Abatan, Abayomi A.; Gutowski, William J., Jr., Iowa State Univ, Dept Geol \& Atmospher Sci, 3134 Agron Hall, Ames, IA 50011 USA.
   Abatan, Abayomi A., Fed Univ Technol Akure, Dept Meteorol \& Climate Sci, Ondo, Nigeria.
   Abiodun, Babatunde J., Univ Cape Town, Dept Environm \& Geog Sci, Climate Syst Anal Grp, Rondebosch, South Africa.
   Rasaq-Balogun, Saidat O., Nigerian Meteorol Agcy, Res \& Training Ctr, Lagos, Nigeria.}},
DOI = {{10.1002/joc.5196}},
ISSN = {{0899-8418}},
EISSN = {{1097-0088}},
Keywords = {{extreme temperature; climate indices; NAO; Nigeria}},
Keywords-Plus = {{ATLANTIC CLIMATE VARIABILITY; MAXIMAL T-TEST; IMPACTS; EVENTS; SHIFTS}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{abatanaa@iastate.edu}},
ORCID-Numbers = {{Abatan, Abayomi/0000-0003-2330-3322}},
Funding-Acknowledgement = {{U.S. National Science Foundation through Earth System Modeling (EaSM)
   {[}AGS-1243030]; Federal University of Technology, Akure, Nigeria}},
Funding-Text = {{We appreciate input from Xiaolan L. Wang and Feng Yang for the provision
   of RClimDex and RHtestsV4 software packages. This work was supported by
   U.S. National Science Foundation through Earth System Modeling (EaSM)
   grant number AGS-1243030 and the Federal University of Technology,
   Akure, Nigeria. All thanks to God for His infinite mercy.}},
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Number-of-Cited-References = {{56}},
Times-Cited = {{9}},
Usage-Count-Last-180-days = {{1}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Int. J. Climatol.}},
Doc-Delivery-Number = {{FU4IO}},
Unique-ID = {{ISI:000423816900007}},
DA = {{2020-08-06}},
}

@article{ ISI:000427359900009,
Author = {DeFlorio, Michael J. and Waliser, Duane E. and Guan, Bin and Lavers,
   David A. and Ralph, F. Martin and Vitart, Frederic},
Title = {{Global Assessment of Atmospheric River Prediction Skill}},
Journal = {{JOURNAL OF HYDROMETEOROLOGY}},
Year = {{2018}},
Volume = {{19}},
Number = {{2}},
Pages = {{409-426}},
Month = {{FEB}},
Abstract = {{Atmospheric rivers (ARs) are global phenomena that transport water vapor
   horizontally and are associated with hydrological extremes. In this
   study, the Atmospheric River Skill (ATRISK) algorithm is introduced,
   which quantifies AR prediction skill in an object-based framework using
   Subseasonal to Seasonal (S2S) Project global hindcast data from the
   European Centre for Medium-Range Weather Forecasts (ECMWF) model. The
   dependence of AR forecast skill is globally characterized by season,
   lead time, and distance between observed and forecasted ARs. Mean values
   of daily AR prediction skill saturate around 7-10 days, and seasonal
   variations are highest over the Northern Hemispheric ocean basins, where
   AR prediction skill increases by 15\%-20\% at a 7-day lead during boreal
   winter relative to boreal summer. AR hit and false alarm rates are
   explicitly considered using relative operating characteristic (ROC)
   curves. This analysis reveals that AR forecast utility increases at
   10-day lead over the North Pacific/western U.S. region during positive
   El Nino-Southern Oscillation (ENSO) conditions and at 7-and 10-day leads
   over the North Atlantic/U.K. region during negative Arctic Oscillation
   (AO) conditions and decreases at a 10-day lead over the North
   Pacific/western U.S. region during negative Pacific-North America (PNA)
   teleconnection conditions. Exceptionally large increases in AR forecast
   utility are found over the North Pacific/western United States at a
   10-day lead during El Nino + positive PNA conditions and over the North
   Atlantic/United Kingdom at a 7-day lead during La Nina + negative PNA
   conditions. These results represent the first global assessment of AR
   prediction skill and highlight climate variability conditions that
   modulate regional AR forecast skill.}},
Publisher = {{AMER METEOROLOGICAL SOC}},
Address = {{45 BEACON ST, BOSTON, MA 02108-3693 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{DeFlorio, MJ (Corresponding Author), CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA.
   DeFlorio, Michael J.; Waliser, Duane E.; Guan, Bin, CALTECH, Jet Prop Lab, Pasadena, CA 91125 USA.
   Waliser, Duane E.; Guan, Bin, Univ Calif Los Angeles, Joint Inst Reg Earth Syst Sci \& Engn, Los Angeles, CA USA.
   Lavers, David A.; Vitart, Frederic, European Ctr Medium Range Weather Forecasts, Reading, Berks, England.
   Ralph, F. Martin, Univ Calif San Diego, Scripps Inst Oceanog, Ctr Western Weather \& Water Extremes, La Jolla, CA 92093 USA.}},
DOI = {{10.1175/JHM-D-17-0135.1}},
ISSN = {{1525-755X}},
EISSN = {{1525-7541}},
Keywords-Plus = {{AMERICAN TELECONNECTION PATTERN; EXTREME PRECIPITATION EVENTS;
   NORTH-ATLANTIC OSCILLATION; SEA-SURFACE TEMPERATURE; UNITED-STATES;
   SOUTH-AMERICA; EL-NINO; FORECAST SKILL; CLIMATE-CHANGE; WEST-COAST}},
Research-Areas = {{Meteorology \& Atmospheric Sciences}},
Web-of-Science-Categories  = {{Meteorology \& Atmospheric Sciences}},
Author-Email = {{michael.deflorio@jpl.nasa.gov}},
ResearcherID-Numbers = {{Guan, Bin/F-6735-2010}},
Funding-Acknowledgement = {{NASA Energy and Water Cycle ProgramNational Aeronautics \& Space
   Administration (NASA); California Department of Water Resources}},
Funding-Text = {{We gratefully acknowledge the availability of the S2S hindcast database
   that makes this work possible. S2S is a joint initiative of the World
   Weather Research Programme (WWRP) and the World Climate Research Program
   (WCRP). The original S2S database is hosted at ECMWF as an extension of
   the ``TIGGE database.'' We would like to acknowledge support from the
   NASA Energy and Water Cycle Program and the California Department of
   Water Resources. We thank the two anonymous reviewers for greatly
   improving the quality of the manuscript. M.D.'s and D.W.'s contributions
   to this study were carried out on behalf of the Jet Propulsion
   Laboratory, California Institute of Technology, under a contract with
   the National Aeronautics and Space Administration.}},
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