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Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China
Future electricity consumption may increase due to climate change, but the amplitude depends on the interaction between many uncertain mechanisms. Based on the linear model and policy model, the residential and commercial electricity consumption in Jiangsu province are projected under the shared soc...
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Published in: | Advances in climate change research 2020-06, Vol.11 (2), p.131-140 |
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creator | Zhang, Mi Cheng, Chin-Hsien Ma, Hong-Yun |
description | Future electricity consumption may increase due to climate change, but the amplitude depends on the interaction between many uncertain mechanisms. Based on the linear model and policy model, the residential and commercial electricity consumption in Jiangsu province are projected under the shared socioeconomic pathways (SSPs). The linear model considers climate and socioeconomic factors, and the policy model also takes policy factors into account. We find that the cooling degree days (CDD) coefficient is about 3 times of heating degree days (HDD), which reflects that the cooling demand is much larger than heating, and also shows in the projection. The results of the policy model are generally lower than the linear model, which is the impact of policy factors. For example, the SSP1 and SSP2 of the policy model are 320 TW h and 241.6 TW h lower than the linear model in 2100, respectively. At the end of the 21st century, the residential and commercial electricity consumption in Jiangsu province will reach 107.7–937.9 TW h per year, 1.3–11.6 times of 2010. The SSP1 scenario under the policy model is based on feasible assumptions, and can be used as the target scenario for policymakers to establish energy intensity reduction targets. |
doi_str_mv | 10.1016/j.accre.2020.06.005 |
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Based on the linear model and policy model, the residential and commercial electricity consumption in Jiangsu province are projected under the shared socioeconomic pathways (SSPs). The linear model considers climate and socioeconomic factors, and the policy model also takes policy factors into account. We find that the cooling degree days (CDD) coefficient is about 3 times of heating degree days (HDD), which reflects that the cooling demand is much larger than heating, and also shows in the projection. The results of the policy model are generally lower than the linear model, which is the impact of policy factors. For example, the SSP1 and SSP2 of the policy model are 320 TW h and 241.6 TW h lower than the linear model in 2100, respectively. At the end of the 21st century, the residential and commercial electricity consumption in Jiangsu province will reach 107.7–937.9 TW h per year, 1.3–11.6 times of 2010. The SSP1 scenario under the policy model is based on feasible assumptions, and can be used as the target scenario for policymakers to establish energy intensity reduction targets.</description><identifier>ISSN: 1674-9278</identifier><identifier>EISSN: 1674-9278</identifier><identifier>DOI: 10.1016/j.accre.2020.06.005</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Climate change ; Electricity consumption ; Projection ; Residential and commercial ; SSP</subject><ispartof>Advances in climate change research, 2020-06, Vol.11 (2), p.131-140</ispartof><rights>2020 National Climate Center (China Meteorological Administration)</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c414t-b13de82b91351eb704f107691885439ab6882a6fdaf8bff95d384305abb52cb3</citedby><cites>FETCH-LOGICAL-c414t-b13de82b91351eb704f107691885439ab6882a6fdaf8bff95d384305abb52cb3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1674927820300332$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3536,27901,27902,45756</link.rule.ids></links><search><creatorcontrib>Zhang, Mi</creatorcontrib><creatorcontrib>Cheng, Chin-Hsien</creatorcontrib><creatorcontrib>Ma, Hong-Yun</creatorcontrib><title>Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China</title><title>Advances in climate change research</title><description>Future electricity consumption may increase due to climate change, but the amplitude depends on the interaction between many uncertain mechanisms. Based on the linear model and policy model, the residential and commercial electricity consumption in Jiangsu province are projected under the shared socioeconomic pathways (SSPs). The linear model considers climate and socioeconomic factors, and the policy model also takes policy factors into account. We find that the cooling degree days (CDD) coefficient is about 3 times of heating degree days (HDD), which reflects that the cooling demand is much larger than heating, and also shows in the projection. The results of the policy model are generally lower than the linear model, which is the impact of policy factors. For example, the SSP1 and SSP2 of the policy model are 320 TW h and 241.6 TW h lower than the linear model in 2100, respectively. At the end of the 21st century, the residential and commercial electricity consumption in Jiangsu province will reach 107.7–937.9 TW h per year, 1.3–11.6 times of 2010. The SSP1 scenario under the policy model is based on feasible assumptions, and can be used as the target scenario for policymakers to establish energy intensity reduction targets.</description><subject>Climate change</subject><subject>Electricity consumption</subject><subject>Projection</subject><subject>Residential and commercial</subject><subject>SSP</subject><issn>1674-9278</issn><issn>1674-9278</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9kM9qGzEQxpeSQkOaJ-hFD1BvRtJKqz30UEzbuAQaSO5i9C_VYktGWgfy9pHtEHrqaWY-5vuY-XXdFwo9BSpv5h6tLb5nwKAH2QOID90lleOwmtioLv7pP3XXtc4AQBUbYRKXXbgvefZ2iTmRHEjxNTqflohbgskRm3c7X-xx9Nu2VqKNy0uTUz3s9ifXITlfyMPDfSUxkd8R01M9kH3JzzFZ_5Ws_8aEn7uPAbfVX7_Vq-7x54_H9e3q7s-vzfr73coOdFhWhnLnFTMT5YJ6M8IQKIxyokqJgU9opFIMZXAYlAlhEo6rgYNAYwSzhl91m3OsyzjrfYk7LC86Y9QnIZcnjWWJdus1s4ggvQxByoE7NY0oKAyMmok7YULL4ucsW3KtxYf3PAr6CF7P-gReH8FrkLqBb65vZ5dvXz5HX3S10TcQLpbGr90R_-t_BX1JjeY</recordid><startdate>202006</startdate><enddate>202006</enddate><creator>Zhang, Mi</creator><creator>Cheng, Chin-Hsien</creator><creator>Ma, Hong-Yun</creator><general>Elsevier B.V</general><general>KeAi Communications Co., Ltd</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>202006</creationdate><title>Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China</title><author>Zhang, Mi ; Cheng, Chin-Hsien ; Ma, Hong-Yun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c414t-b13de82b91351eb704f107691885439ab6882a6fdaf8bff95d384305abb52cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Climate change</topic><topic>Electricity consumption</topic><topic>Projection</topic><topic>Residential and commercial</topic><topic>SSP</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Mi</creatorcontrib><creatorcontrib>Cheng, Chin-Hsien</creatorcontrib><creatorcontrib>Ma, Hong-Yun</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Directory of Open Access Journals</collection><jtitle>Advances in climate change research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Mi</au><au>Cheng, Chin-Hsien</au><au>Ma, Hong-Yun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China</atitle><jtitle>Advances in climate change research</jtitle><date>2020-06</date><risdate>2020</risdate><volume>11</volume><issue>2</issue><spage>131</spage><epage>140</epage><pages>131-140</pages><issn>1674-9278</issn><eissn>1674-9278</eissn><abstract>Future electricity consumption may increase due to climate change, but the amplitude depends on the interaction between many uncertain mechanisms. Based on the linear model and policy model, the residential and commercial electricity consumption in Jiangsu province are projected under the shared socioeconomic pathways (SSPs). The linear model considers climate and socioeconomic factors, and the policy model also takes policy factors into account. We find that the cooling degree days (CDD) coefficient is about 3 times of heating degree days (HDD), which reflects that the cooling demand is much larger than heating, and also shows in the projection. The results of the policy model are generally lower than the linear model, which is the impact of policy factors. For example, the SSP1 and SSP2 of the policy model are 320 TW h and 241.6 TW h lower than the linear model in 2100, respectively. At the end of the 21st century, the residential and commercial electricity consumption in Jiangsu province will reach 107.7–937.9 TW h per year, 1.3–11.6 times of 2010. The SSP1 scenario under the policy model is based on feasible assumptions, and can be used as the target scenario for policymakers to establish energy intensity reduction targets.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.accre.2020.06.005</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Climate change Electricity consumption Projection Residential and commercial SSP |
title | Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China |
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