Non-technological and behavioral options for decarbonizing buildings – A review of global topics, trends, gaps, and potentials-Reference-Cited by-同舟云学术

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Non-technological and behavioral options for decarbonizing buildings – A review of global topics, trends, gaps, and potentials

Published:2022-01 Issue: Volume:29 Page:529-545
ISSN:2352-5509
Container-title:Sustainable Production and Consumption
language:en
Short-container-title:Sustainable Production and Consumption

Author:

Mata É.,Kihila J.M.,Wanemark J.,Cheng S.H.,Harris S.,Sandkvist F.,Nyberg T.,Yaramenka K.

Funder

Energimyndigheten

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Renewable Energy, Sustainability and the Environment,Environmental Chemistry,Environmental Engineering

Reference150 articles.

1. From Principles to Practices;Acharya,2018

2. Occupant behavior for energy conservation in commercial buildings: lessons learned from competition at the Oak Ridge National Laboratory;Ahl;Sustainability,2019

3. To each their own? The greenhouse gas impacts of intra-household sharing in different urban zones;Ala-Mantila;J. Clean. Prod.,2016

4. Energy use, behavioral change, and business organizations: reviewing recent findings and proposing a future research agenda;Andrews;Energy Res. Soc. Sci.,2016

5. Understanding occupant behaviors in dynamic environments using OBiDE framework;Arslan;Build. Environ.,2019

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1. Occupant‐Driven Urban Building Energy Efficiency via Ambient Intelligence;Artificial Intelligence in Performance‐Driven Design;2024-04-19

2. Twin transition in the built environment – Policy mechanisms, technologies and market views from a cold climate perspective;Sustainable Cities and Society;2023-11

3. Total CO2 emissions associated with buildings in 266 Chinese cities: characteristics and influencing factors;Resources, Conservation and Recycling;2023-01

4. Dynamic scenario simulations of phased carbon peaking in China's building sector through 2030–2050;Sustainable Production and Consumption;2023-01

5. DR Participants’ Actual Response Prediction Using Artificial Neural Networks;Lecture Notes in Networks and Systems;2022-10-12

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