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Dennies Bor

Publications and source records attributed to Dennies Bor.

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Assessing the economic benefits of space weather mitigation investment decisions: Evidence from Aotearoa New Zealand

Space weather events pose a growing threat to modern economies, yet their macroeconomic consequences remain underexplored. This study presents the first dedicated economic assessment of geomagnetic storm impacts on Aotearoa New Zealand, quantifying potential gross domestic product (GDP) losses across seven conservative disruption and mitigation scenarios due to an extreme coronal mass ejection (CME). The primary focus is on the damaging impacts of geomagnetically induced currents (GICs) on the electrical power transmission network. We support space weather mitigation investment decisions by providing a first-order approximation of their potential economic benefits, using best-in-class scientific models, via a coupled physics-engineering-economic spatial modelling framework. Recognising uncertainty in the economic interpretation of power outage impacts, we compare four different estimation methods. In the most severe unmitigated scenario, estimated GDP losses reach NZD3.58 billion (0.98 percent of annual GDP). Targeted GIC-informed scenarios still produce material losses, with no mitigation reaching up to NZD1.48 billion (0.41 percent of annual GDP). Mitigation substantially reduces these impacts. Operational strategies, including optimized switching and islanding, achieve benefit-cost ratios as high as 330 to 1, while physical protections such as GIC blocking devices produce returns up to 34.4 to 1. When also acknowledging additional unmodelled impacts, including multi-billion losses in capital equipment and long-term revenue, the economic rationale for pre-emptive mitigation becomes even more pertinent.

physics.geo-ph

Quantifying polarization across political groups on key policy issues using sentiment analysis

There is growing concern that over the past decade, industrialized democratic nations are becoming increasingly politically polarized. Indeed, elections in the US, UK, France, and Germany have all seen tightly won races, with notable examples including the 2016 Trump vs. Clinton presidential election and the UK's Brexit referendum. However, while there has been much qualitative discussion of polarization on key issues, there are few examples of formal quantitative assessments examining this topic. Therefore, in this paper, we undertake a statistical evaluation of political polarization for representatives elected to the US congress on key policy issues between 2021-2022. The method is based on applying sentiment analysis to Twitter data and developing quantitative analysis for six political groupings defined based on voting records. Two sets of policy groups are explored, including geopolitical policies (e.g., Ukraine-Russia, China, Taiwan, etc.) and domestic policies (e.g., abortion, climate change, LGBTQ, immigration, etc.). We find that out of the twelve policies explored here, gun control was the most politically polarizing, with significant polarization results found for all groups (four of which were P < 0.001). The next most polarizing issues include immigration and border control, fossil fuels, and Ukraine-Russia. Interestingly, the least polarized policy topics were Taiwan, LGBTQ, and the Chinese Communist Party, potentially demonstrating the highest degree of bipartisanship on these issues. The results can be used to guide future policy making, by helping to identify areas of common ground across political groups.

stat.AP