TY - JOUR
T1 - Emergence of urban clustering among U.S. cities under environmental stressors
AU - Wang, Chenghao
AU - Wang, Zhi Hua
AU - Li, Qi
N1 - Funding Information:
This work was supported by the U.S. National Science Foundation (NSF) under grant number AGS-1930629 . We would like to thank the handing editor and three anonymous reviewers for their constructive feedback and help in improving the quality of the manuscript.
Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/12
Y1 - 2020/12
N2 - Cities are the hotspots of global human–environment interactions, and their sustainable development requires proactive strategies to mitigate and adapt to emergent environmental issues. Nevertheless, most of the existing studies and strategies are based on specific (and often singular) environmental processes, and their efficacy is largely undermined by their heavy dependence on locality. Here we present a novel modeling framework for urban studies to capture spatial connectivity and teleconnection among cities in response to different environmental stressors. For illustration, a generic message-passing-based algorithm is used to identify spatial structures among U.S. cities. Urban structures are analyzed under two types of environmental stressors, i.e., extreme heat and air pollution, based on remotely sensed land surface temperature data during short-term heat wave events and a yearlong remotely sensed aerosol optical depth dataset, respectively. Results show that U.S. cities are clustered as locally and regionally connected groups, while the hub–periphery organization manifest via environmental similarity and atmospheric transport under both event-scale meteorological extremes and long-term environmental stressors. The physics-driven urban agglomeration reveals that cities are multilevel interconnected complex systems rather than isolated entities. The proposed framework provides a new pathway to shift goal- or process-based urban studies to system-based global ones.
AB - Cities are the hotspots of global human–environment interactions, and their sustainable development requires proactive strategies to mitigate and adapt to emergent environmental issues. Nevertheless, most of the existing studies and strategies are based on specific (and often singular) environmental processes, and their efficacy is largely undermined by their heavy dependence on locality. Here we present a novel modeling framework for urban studies to capture spatial connectivity and teleconnection among cities in response to different environmental stressors. For illustration, a generic message-passing-based algorithm is used to identify spatial structures among U.S. cities. Urban structures are analyzed under two types of environmental stressors, i.e., extreme heat and air pollution, based on remotely sensed land surface temperature data during short-term heat wave events and a yearlong remotely sensed aerosol optical depth dataset, respectively. Results show that U.S. cities are clustered as locally and regionally connected groups, while the hub–periphery organization manifest via environmental similarity and atmospheric transport under both event-scale meteorological extremes and long-term environmental stressors. The physics-driven urban agglomeration reveals that cities are multilevel interconnected complex systems rather than isolated entities. The proposed framework provides a new pathway to shift goal- or process-based urban studies to system-based global ones.
KW - Aerosol optical depth
KW - Air pollution
KW - Atmospheric teleconnection
KW - Heat waves
KW - Land surface temperature
KW - Urban sustainability
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U2 - 10.1016/j.scs.2020.102481
DO - 10.1016/j.scs.2020.102481
M3 - Article
AN - SCOPUS:85092534749
VL - 63
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
SN - 2210-6707
M1 - 102481
ER -