Building energy consumption reduction driven by the accessibility to greenspace ecological effect

Zhuoqun Zhao; Hong Ye; Kai Wang; Tao Lin; Guoqin Zhang; Meixia Lin

Ecological Indicators (Mar 2024)

Building energy consumption reduction driven by the accessibility to greenspace ecological effect

Zhuoqun Zhao,
Hong Ye,
Kai Wang,
Tao Lin,
Guoqin Zhang,
Meixia Lin

Affiliations

Zhuoqun Zhao: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Haixi Industrial Technology Innovation Center in Beilun, Ningbo 315800, China; Fujian Key Laboratory of Digital Technology for Territorial Space Analysis and Simulation, Fuzhou 350108, China; Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China
Hong Ye: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Haixi Industrial Technology Innovation Center in Beilun, Ningbo 315800, China; Fujian Key Laboratory of Digital Technology for Territorial Space Analysis and Simulation, Fuzhou 350108, China; Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China; Corresponding author.
Kai Wang: China-UK Low Carbon College, Shanghai Jiao Tong University, Shanghai 200240, China
Tao Lin: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; Fujian Key Laboratory of Digital Technology for Territorial Space Analysis and Simulation, Fuzhou 350108, China; Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China
Guoqin Zhang: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; CAS Haixi Industrial Technology Innovation Center in Beilun, Ningbo 315800, China; Fujian Key Laboratory of Digital Technology for Territorial Space Analysis and Simulation, Fuzhou 350108, China; Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China
Meixia Lin: Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China; Fujian Key Laboratory of Digital Technology for Territorial Space Analysis and Simulation, Fuzhou 350108, China; Xiamen Key Laboratory of Smart Management on the Urban Environment, Xiamen 361021, China

Journal volume & issue: Vol. 160
p. 111750

Abstract

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Rapid urbanization leads to a discrepancy between building operational energy consumption carbon emissions (BECCE) and urban sustainable development. Urban greenspace, which modifies local microclimates and thus BECCE, plays a critical part in reducing BECCE. To improve our scientific understanding and further explore the ecological effect of urban greenspace landscape pattern on BECCE, this study proposed an innovative method for modeling the accessibility to greenspace ecological effect to reduce BECCE. Accessibility was calculated using source–sink landscape theory as the theoretical basis and an improved potential model as the numerical basis. The normalized compactness index was adopted to measure the overall resistance to the ecological process and consider compact urban morphology. A case study of 67 office buildings in China demonstrated the applicability and implications of the model. The study found that i) total area and landscape shape index of greenspace, which represent source accessibility, are both significantly negatively correlated with BECCE; ii) landscape shape index of greenspace, which represents source accessibility and reflects greenspace landscape complexity, figures prominently in building carbon reductions and improves model predictions. The newly developed model can be used to identify optimal arrangements of urban green infrastructure to reduce BECCE under current conditions of intense urban land use, make projections of carbon emissions, and support decision makers in implementing nature-based solutions to achieve carbon emission peak and carbon neutrality goals.

Published in Ecological Indicators

ISSN: 1470-160X (Print); 1872-7034 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Science: Biology (General): Ecology
Website: https://www.sciencedirect.com/journal/ecological-indicators

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