Socioeconomic and Housing Vulnerability’s Role in Decision Time for Reconstruction in Puerto Rico after Hurricane Maria

Sarker, Tonmoy; Poleacovschi, Cristina; García, Ivis; Weems, Carl F.; Ikuma, Kaoru; Rehmann, Chris R.

doi:10.1061/9780784483954.047

Cited by 1 publication

(1 citation statement)

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“…However, according to forensic engineers interviewed in the study, building damage repairs are arduous for many homeowners due to inflation, difficulty in getting insurance claims, incompatibility of old and new materials, and expensive new construction methods. Additionally, lower-income homeowners are less likely to start reconstruction or repair due to their struggle to gain access to federal funding and recovery resources [54]. Maldonado et al (2016) highlighted that across the country, communities of color and low-income communities who reside in hurricane-prone areas do not have the financial resources or access to credit to make their homes safer before a disaster (e.g., by raising a home on pilings to avoid floodwaters) [55].…”

Section: Discussionmentioning

confidence: 99%

Revamping Sustainability Efforts Post-Disaster by Adopting Circular Economy Resilience Practices

Pradhananga,

ElZomor

2023

Sustainability

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Post-disaster reconnaissance is vital for assessing the impact of a natural disaster on the built environment and informing improvements in design, construction, risk mitigation, and our understanding of extreme events. The data obtained from reconnaissance can also be utilized to improve disaster recovery planning by maximizing resource efficiency, minimizing waste, and promoting resilience in future disasters. This paper aims to investigate existing reconnaissance reports and datasets to identify the factors that impact the reusability of buildings post-disaster and to recommend strategies that align with circular economy goals. The study adopted a three-step research methodology to attain the proposed goals: (1) thematic analysis was used to evaluate types of damages reported in the reconnaissance reports; (2) a supervised machine-learning algorithm was employed to analyze reconnaissance datasets; and (3) a concept map was developed based on interviews of 109 stakeholders in disaster-prone communities to recommend strategies to adopt circular economy practices post-disaster. The study results highlight the recurring risks of damage to different parts of the building and how circular economy resilience practices like deconstruction can minimize waste and maximize resource efficiency during post-disaster recovery. The findings of the study promote a more regenerative economy to build resilience to the challenges of future extreme weather events.

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Section: Discussionmentioning

confidence: 99%