Urban functional area building carbon emission reduction driven by three-dimensional compact urban forms’ optimization

• Propose urban functional area division method for building operation energy consumption. • Three-dimensional compactness significantly affects building operation energy consumption. • Residential, commercial and industrial functional areas have individual energy reduction path. • Building energy reduction methods exhibited discrepancies across urban functional areas. Previous optimization approaches with regard to the overall urban form can no longer meet the demand for accurately implementing building energy consumption carbon emission reduction at small spatial scales. This study constructed building energy consumption-oriented urban functional area division method using points of point-of-interest (POI), three-dimensional building and roadway data with urban functional areas as units. The method linked POI to buildings, using building volume as an auxiliary parameter to determine the functional attributes of blocks while taking into account the building operational energy consumption. The residential functional areas, commercial functional areas and industrial functional areas, which account for more than 90% of the total building operation energy consumption and the top three in terms of share, are selected as the analysis objects. Geographic detector was applied to analyze the mechanism of carbon metabolism in the compact spatial patterns of these three functional areas. The case study in Xiamen, China reveals that (1) Three-dimensional building compactness is an important factor influencing building energy consumption(normalized difference vegetation index q-value is 0.227); (2) the difference in energy consumption between different compactness classes in residential and commercial functional areas is significant, while not in industrial functional areas; (3) according to the three-dimensional building compactness optimization path of this study, the building operation energy consumption in central Xiamen City could be optimized to reduce by 7% in 2015. Based on the self-created building energy consumption-oriented functional area division method, it is concluded at the functional areas scale that different types of urban functional zones have different optimization methods for three-dimensional building compactness. Such optimization can save construction resources and achieve double carbon more effectively.

Authors

Institutions

Publication Details

Journal
Ecological Indicators
Published
2024-09-16
DOI
https://doi.org/10.1016/j.ecolind.2024.112614
Citations
12
Primary Topic
Urban Design and Spatial Analysis
Type
article
Field-Weighted Citation Impact
3.18
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Urban functional area building carbon emission reduction driven by three-dimensional compact urban forms’ optimization

Xian Wu, Guoqin Zhang, Zhuoqun Zhao, Mengran Zhou et al.
12 citations
Ecological Indicators
Urban Design and Spatial Analysis
3.18
article

Urban functional area building carbon emission reduction driven by three-dimensional compact urban forms’ optimization

Xian Wu, Guoqin Zhang, Zhuoqun Zhao, Mengran Zhou, Rui Jing, Han Yan, Tao Lin, Ye Hong, Huanye He
article en
12 citations

Abstract

• Propose urban functional area division method for building operation energy consumption. • Three-dimensional compactness significantly affects building operation energy consumption. • Residential, commercial and industrial functional areas have individual energy reduction path. • Building energy reduction methods exhibited discrepancies across urban functional areas. Previous optimization approaches with regard to the overall urban form can no longer meet the demand for accurately implementing building energy consumption carbon emission reduction at small spatial scales. This study constructed building energy consumption-oriented urban functional area division method using points of point-of-interest (POI), three-dimensional building and roadway data with urban functional areas as units. The method linked POI to buildings, using building volume as an auxiliary parameter to determine the functional attributes of blocks while taking into account the building operational energy consumption. The residential functional areas, commercial functional areas and industrial functional areas, which account for more than 90% of the total building operation energy consumption and the top three in terms of share, are selected as the analysis objects. Geographic detector was applied to analyze the mechanism of carbon metabolism in the compact spatial patterns of these three functional areas. The case study in Xiamen, China reveals that (1) Three-dimensional building compactness is an important factor influencing building energy consumption(normalized difference vegetation index q-value is 0.227); (2) the difference in energy consumption between different compactness classes in residential and commercial functional areas is significant, while not in industrial functional areas; (3) according to the three-dimensional building compactness optimization path of this study, the building operation energy consumption in central Xiamen City could be optimized to reduce by 7% in 2015. Based on the self-created building energy consumption-oriented functional area division method, it is concluded at the functional areas scale that different types of urban functional zones have different optimization methods for three-dimensional building compactness. Such optimization can save construction resources and achieve double carbon more effectively.

Ecological IndicatorsVol. 167
Xiamen University (CN), Chinese Academy of Sciences (CN), Institute of Urban Environment (CN), University of Chinese Academy of Sciences (CN)
Sustainable cities and communities, Climate action
Openalex Percentile: Top 8%
Urban Design and Spatial Analysis
3.18
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.