Latest paper from our lab led by @libo0901 and @Chao_Fan__ explores disparities in PM2.5 air pollution exposure among income groups using billions of anonymized, privacy-enhanced mobile phone data. Our findings reveal that low-income populations face disproportionate exposure due to mobility patterns, including frequent visits to industrial areas and larger mobility scales for daily needs.
The findings highlight critical environmental justice and public health challenges, offering fresh insights for mitigating inequality in urban pollution exposure.
https://t.co/aRBEHfieVN
📢New pre-print from our lab led by @libo0901 presents a comprehensive study analyzing the vulnerability of the U.S. power infrastructure over the past decade. Our research, based on over 179 million power outage records across 3,022 counties from 2014-2023, reveals a troubling trend: the frequency, intensity, and duration of power outages are increasing, especially in socially vulnerable areas. Coastal regions like California, Florida, and New Jersey are particularly hard-hit.
This data-driven analysis underscores the urgent need for policies that enhance the resilience of our power systems.
https://t.co/bCS9qEnznB
New preprint from our lab led by @libo0901 examines inequality in infrastructure quality provision in cities. Departing from the existing approaches focusing on infrastructure quantity and index-based methods, We adopted a machine learning approach to evaluate infrastructure quality based on how it affects exposure to environmental hazards like air pollution and urban heat. This approach enables integrated urban design strategies that promote environmental justice through infrastructure development #InfrastructureEquity #UrbanAI #ML
https://t.co/eWJ4Sn7di2
A new preprint led by @libo0901 reveal #Resilience curve archetypes & their fundamental properties in power infrastructure using unsupervised #MachineLearning. Findings explain distinct resilience behaviors of triangular vs trapezoidal archetypes.
https://t.co/Ia6FJGeRkv
New preprint from our lab led by @libo0 in collaboration with @Chao_Fan__ examined how human network dynamics influence population flood exposure 👇
https://t.co/6ZeYt5NEL3