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Author:

Menghan Niu (Menghan Niu.) | Ying Ji (Ying Ji.) | Miao Zhao (Miao Zhao.) | Jiefan Gu (Jiefan Gu.) | Aonan Li (Aonan Li.)

Abstract:

Along with the improvement of social productivity and living standard,residential buildings generate a growing portion of carbon emissions,especially during the operation stage.However,energy use behaviors are usually ignored in carbon emission calculation.This study focuses on calculating carbon emissions during the operation stage for residential buildings based on the characteristics of energy use behaviors in different regions.Firstly,we investigated energy use behaviors in dwellings across three cities in China:Xi'an,Shanghai and Fuzhou.Then,we established calibrated carbon emission models and optimization models with different green building measures for residential buildings.The results of this research reveal a significant disparity between the energy usage habits of residents in different climate regions.The carbon emissions of residential electricity bills in Xi'an,Shanghai and Fuzhou are 13.6 kgCO2/(m2·a)(excluding central heating),29.3 kgCO2/(m2·a)and 17.2 kgCO2/(m2·a),respectively.Equipment carbon emissions account for 32.2%-64.1%of the total.In comparison to the model based on internal standard setting,the accuracy of the models using actual internal has improved by 25.9%-37.4%.The three-star green building methods have the highest carbon reduction rate among different star buildings,the emission reduction rates are around 30%.This study's findings are useful for carbon emission calculation and green building design of residential buildings in the future.

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Author Community:

  • [ 1 ] [Ying Ji]北京工业大学
  • [ 2 ] [Aonan Li]The Bartlett School of Architecture,University College London,WC1E6BT,UK
  • [ 3 ] [Miao Zhao]北京工业大学
  • [ 4 ] [Menghan Niu]北京工业大学
  • [ 5 ] [Jiefan Gu]College of Architecture and Urban Planning,Tongji University,Shanghai201804,China

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Source :

建筑模拟(英文版)

ISSN: 1996-3599

Year: 2024

Issue: 1

Volume: 17

Page: 147-164

5 . 5 0 0

JCR@2022

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count: -1

Chinese Cited Count:

30 Days PV: 9

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