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Impact of truck electrification on air pollution disparities in the United States
Electrifying heavy-duty trucks reduces on-road diesel emissions but shifts the burden of supplying energy to power-generation facilities. The combined effect of Inflation Reduction Act investments in grid decarbonization and truck electrification will alter the magnitude and distribution of air pollution burdens across the United States. These investments are intended to facilitate a just energy transition, with 40% of the benefits flowing to disadvantaged communities per the Justice40 Initiative. Here we evaluate the combined effects of Inflation Reduction Act grid decarbonization and truck electrification investments on a national scale to determine whether the air pollution benefits would meet this 40% goal for both disadvantaged communities and the most exposed racial–ethnic groups. We find that truck electrification and decarbonization reduce air-pollution-related premature mortality in disadvantaged communities. However, the relative disparity between disadvantaged and non-disadvantaged communities increases, suggesting that a disproportionate share of benefits accrue to non-disadvantaged communities. Whereas absolute disparity in grid emissions decreases over time for all racial–ethnic groups, relative disparity remains largely unchanged, with Black populations being the most exposed. Electrifying drayage corridors would result in comparatively large health benefits for disadvantaged communities, suggesting that increasing targeted electrification investments in short-haul routes near urban areas (for example, ports) could be promising.
Socially vulnerable communities face disproportionate exposure and susceptibility to U.S. wildfire and prescribed burn smoke
While air pollution from most U.S. sources has decreased, emissions from wildland fires have risen. Here, we use an integrated assessment model to estimate that wildfire and prescribed burn smoke caused $200 billion in health damages in 2017, associated with 20,000 premature deaths. Nearly half of this damage came from wildfires, predominantly in the West, with the remainder from prescribed burns, mostly in the Southeast. Our analysis reveals positive correlations between smoke exposure and various social vulnerability measures; however, when also considering smoke susceptibility, these disparities are systematically influenced by age. Senior citizens, who are disproportionately White, represented 16% of the population but incurred 75% of the damages. Nonetheless, within most age groups, Native American and Black communities experienced the greatest damages per capita. Our work highlights the extraordinary and disproportionate effects of the growing threat of fire smoke and calls for targeted, equitable policy solutions for a healthier future.
Social disparities in neighborhood flood exposure in 44,698 urban neighborhoods in Latin America
Climate change is expected to greatly increase exposure to flooding, particularly among urban populations in low- and middle-income countries. Here we used daily flood data (2000–2018) to describe socioeconomic disparities in flooding on the basis of neighborhood educational attainment, comparing disparities across and within cities. We used multilevel models to examine disparities in area flooding by city- and neighborhood-level factors, including 44,698 neighborhoods in 276 cities from eight countries with a total of 223 million residents and 117 distinct flood events. One in 4 of residents of neighborhoods in the lowest quintile of educational attainment were exposed to flooding, compared with 1 in 20 residents of neighborhoods in the highest quintile of educational attainment. Neighborhoods experiencing more flooding included those with lower educational attainment, that were coastal, less dense, further from the city center and greener, and that had steeper slopes. We show large social disparities in neighborhood flooding within Latin American cities. Policymakers must prioritize flood adaptation and recovery efforts in neighborhoods with lower socioeconomic status.
Leveraging large language models to assist philosophical counseling: prospective techniques, value, and challenges
Large language models (LLMs) have emerged as transformative tools with the potential to revolutionize philosophical counseling. By harnessing their advanced natural language processing and reasoning capabilities, LLMs offer innovative solutions to overcome limitations inherent in traditional counseling approaches—such as counselor scarcity, difficulties in identifying mental health issues, subjective outcome assessment, and cultural adaptation challenges. In this study, we explore cutting‐edge technical strategies—including prompt engineering, fine‐tuning, and retrieval‐augmented generation—to integrate LLMs into the counseling process. Our analysis demonstrates that LLM-assisted systems can provide counselor recommendations, streamline session evaluations, broaden service accessibility, and improve cultural adaptation. We also critically examine challenges related to user trust, data privacy, and the inherent inability of current AI systems to genuinely understand or empathize. Overall, this work presents both theoretical insights and practical guidelines for the responsible development and deployment of AI-assisted philosophical counseling practices.
Global disparities in drug-related adverse events of patients with multiple myeloma: a pharmacovigilance study
Multiple myeloma (MM) is a complex hematological malignancy of clonal plasma cells driven by alterations to the chromosomal material leading to uncontrolled proliferation in the bone marrow. Ethnic and racial disparities persist in the prevalence, diagnosis, management, and outcomes of MM. These disparities are multifaceted and intersect with various factors, including demographics, geography, socioeconomic status, genetics, and access to healthcare. This study utilized the openFDA human drug adverse events (AEs) to analyze global data pertaining to MM patients and patterns of treatment-related AEs. We identified ten most frequently used drugs and drug regimens in six distinct regions, including North America (NA), Europe (EU), Asia (AS), Africa (AF), Oceania (OC), and Latin America & the Caribbean (LA). AE patterns were evaluated using the reporting odds ratio combined with a 95% confidence interval. AE reports were more prevalent in men than in women across all regions. Cardiotoxicities were more likely observed in AS and EU, while secondary neoplasms were more frequently reported in the EU. Nephropathies were prominent in OC, AF (in males), and AS (in females), while vascular toxicity, including embolism and thrombosis, was more common in NA (in males). A notable improvement in survival, particularly in AS, EU, and NA, with a significant decline in death rates was observed. Hospitalization rates displayed less variation in AS and EU but exhibited more pronounced fluctuations in AF, LA, and OC. In conclusion, this comprehensive analysis offers valuable insights into the demographic, geographic, and AE patterns of MM patients across the globe.
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