The statistical analysis and prediction associated with nuclear meltdown accidents risk evaluation

He, Bowen; Guan, Qun

doi:10.1504/ijnss.2022.127918

Cited by 5 publications

(1 citation statement)

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“…Climate change has become a severe problem for the modern world. Extensive studies have found that climate change can influence every aspect of society, from community vulnerability and resilience [1][2][3][4] to fresh water and climate ecosystems [5][6][7][8][9]. To address the climate crisis, electric vehicles (EVs) have been adopted worldwide to help fight climate change by reducing emissions compared to conventional gasoline vehicles (CVs) [7,10].…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Lithium-Ion Battery (LiB) Recycling Technologies and Industrial Market Trend Insights

He,

Zheng,

Tang

et al. 2024

Recycling

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Adopting EVs has been widely recognized as an efficient way to alleviate future climate change. Nonetheless, the large number of spent LiBs associated with EVs is becoming a huge concern from both environmental and energy perspectives. This review summarizes the three most popular LiB recycling technologies, the current LiB recycling market trend, and global recycling magnates’ industrial dynamics regarding this subject. We mainly focus on reviewing hydrometallurgical and direct recycling technologies to discuss the advancement of those recycling technologies and their future commercialization pathway.

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Section: Introductionmentioning

confidence: 99%

A Comprehensive Review of Lithium-Ion Battery (LiB) Recycling Technologies and Industrial Market Trend Insights

He,

Zheng,

Tang

et al. 2024

Recycling

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Incorporating spatial autocorrelation in dasymetric mapping: A hierarchical Poisson spatial disaggregation regression model

He,

Gilligan,

Camp

2024

Applied Geography

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Investigating the effects of spatial scales on social vulnerability index: A hybrid uncertainty and sensitivity analysis approach combined with remote sensing land cover data

He,

Guan

2024

Risk Analysis

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Investigating the effects of spatial scales on the uncertainty and sensitivity analysis of the social vulnerability index (SoVI) model output is critical, especially for spatial scales finer than the census block group or census block. This study applied the intelligent dasymetric mapping approach to spatially disaggregate the census tract scale SoVI model into a 300‐m grids resolution SoVI map in Davidson County, Nashville. Then, uncertainty analysis and variance‐based global sensitivity analysis were conducted on two scales of SoVI models: (a) census tract scale; (b) 300‐m grids scale. Uncertainty analysis results indicate that the SoVI model has better confidence in identifying places with a higher socially vulnerable status, no matter the spatial scales in which the SoVI is constructed. However, the spatial scale of SoVI does affect the sensitivity analysis results. The sensitivity analysis suggests that for census tract scale SoVI, the indicator transformation and weighting scheme are the two major uncertainty contributors in the SoVI index modeling stages. While for finer spatial scales like the 300‐m grid's resolution, the weighting scheme becomes the uttermost dominant uncertainty contributor, absorbing uncertainty contributions from indicator transformation.

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The statistical analysis and prediction associated with nuclear meltdown accidents risk evaluation

Cited by 5 publications

References 0 publications

A Comprehensive Review of Lithium-Ion Battery (LiB) Recycling Technologies and Industrial Market Trend Insights

A Comprehensive Review of Lithium-Ion Battery (LiB) Recycling Technologies and Industrial Market Trend Insights

Incorporating spatial autocorrelation in dasymetric mapping: A hierarchical Poisson spatial disaggregation regression model

Investigating the effects of spatial scales on social vulnerability index: A hybrid uncertainty and sensitivity analysis approach combined with remote sensing land cover data

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