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      Spatiotemporal distribution of green-certified buildings and the influencing factors: A study of U.S.

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          Abstract

          Green building development is a global strategic plan aimed at addressing environmental burdens and reducing energy consumption in the building sector. Currently, research does not adequately reveal the spatiotemporal patterns of green-certified building development and the factors that influence it. To address this gap, this study investigates the dynamic distribution of Leadership in Energy and Environmental Design (LEED) certified projects in the U.S. by incorporating time effects into spatial regression models. The results reveal that (1) significant regional variations in the spatiotemporal distribution of green-certified buildings (global Moran's index for 2017, 2019 and 2021 are 0.0172, 0.0327 and 0.0622 respectively). (2) Demographic, socioeconomic, environmental, and policymaking factors explain the observed patterns (the mean values of the coefficients of population size, the Caucasian demographic proportion to the total population, income inequality, regional price parity, and average annual temperature were 8236.1383, −18.9113, −533.1024, 365.1813 and 227.1735 respectively). (3) Expedited permitting, reduced fees, and property tax credit or exemption (p-values less than 0.01) are significant policy instruments that promote the implementation of LEED certified projects. The findings offer pivotal insights that enable targeted interventions, informed decisions, and effective resource allocation. Furthermore, it furnishes a reference for strategically siting green building initiatives in the next phase, encompassing zero-energy buildings, green technologies, and low-carbon solutions. Enhancing understanding of complexities in U.S. green-certified building practices, this research acts as an evidence-based cornerstone across sectors. Urban planners can leverage these insights to allocate resources efficiently and steer green-certified projects, for impactful environmental sustainability and community progress. Policymakers can customize incentives based on drivers of adoption, promoting equitable distribution. Meanwhile, construction stakeholders can optimize strategies through decoding temporal and spatial adoption patterns, leading to prudent resource use and project success.

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          Highlights

          • This study thoroughly investigates the spatiotemporal dynamics of green building adoption.

          • It illuminates temporal and spatial variations of green buildings across different building types and certification levels.

          • The geographically and temporally weighted regression model elucidates the spatiotemporal heterogeneity.

          • Expedited permitting, reduced fees, and property tax credit or exemption are important.

          • Policy recommendations based on the spatiotemporal heterogeneity and influencing factors.

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          Most cited references60

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          Scientometric review of global research trends on green buildings in construction journals from 1992 to 2018

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            Sustainable consumption in the circular economy. An analysis of consumers’ purchase intentions for waste-to-value food

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              Towards the next generation of green building for urban heat island mitigation: Zero UHI impact building

              Bao-Jie He (2019)
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                31 October 2023
                November 2023
                31 October 2023
                : 9
                : 11
                : e21868
                Affiliations
                [1]School of Urban Design, Wuhan University, Wuhan, China
                Author notes
                []Corresponding author. zh.gou@ 123456whu.edu.cu
                Article
                S2405-8440(23)09076-X e21868
                10.1016/j.heliyon.2023.e21868
                10660489
                968d8a5e-8999-41f7-bff0-4a9719fcf754
                © 2023 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 June 2023
                : 8 October 2023
                : 30 October 2023
                Categories
                Research Article

                green building,spatiotemporal distribution,energy policy,geographical and temporal weighted regression,demographic and socioeconomic factors

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