Anthropogenic influence on extremes and risk hotspots

Volunteerism Addressing Environmental Disparities in Allergy (VAEDIA): The presidential initiative to combat environmental injustice in allergy and immunology-a Work Group Report of the AAAAI VAEDIA task force

Many vulnerable people lose their health or lives each year as a result of unhealthy environmental conditions that perpetuate medical conditions within the scope of allergy and immunology specialists' expertise. While detrimental environmental factors impact all humans globally, the effect is disproportionately more profound in impoverished neighborhoods. Environmental injustice is the inequitable exposure of disadvantaged populations to environmental hazards. Professional medical organizations such as the American Academy of Allergy, Asthma & Immunology (AAAAI) are well positioned to engage and encourage community outreach volunteer programs to combat environmental justice. Here we discuss how environmental injustices and climate change impacts allergic diseases among vulnerable populations. We discuss pathways allergists/immunologists can use to contribute to addressing environmental determinants by providing volunteer clinical service, education, and advocacy. Furthermore, allergists/immunologists can play a role in building trust within these communities, partnering with other patient advocacy nonprofit stakeholders, and engaging with local, state, national, and international nongovernmental organizations, faith-based organizations, and governments. The AAAAI's Volunteerism Addressing Environmental Disparities in Allergy (VAEDIA) is the presidential task force aiming to promote volunteer initiatives by creating platforms for discussion and collaboration and by funding community-based projects to address environmental injustice.

Evolutionary analysis of rainstorm momentum and non-stationary variating patterns in response to climatic changes across diverse terrains

This study aims to analyze time-series measurements encompassing rainstorm events with over a century of datasets to identify rainstorm evolution and dimensional transitions in non-stationarity. Rainstorm events are identified using partial duration series (PDS) to extract changes in rainstorm characteristics, namely maximum intensity (MAXI), duration (D), total rainfall (TR), and average rainfall intensity (ARI), in response to climate change. Ensemble empirical mode decomposition is used for trend filtering and non-stationary identification to explore spatiotemporal insight patterns. Trend models for the first-second-order moments of rainstorm characteristics are used to formulate the identified mean-variance trends using combined multi-dimensional linear-parabolic regression. Best-fitting combinations of various distributions (probability density functions) and trend models for multiple characteristic series are identified based on the Akaike information criterion. We analyze the dimensional transition in rainfall non-stationarity based on sensitivity analysis using PDS to determine its natural geophysical causes. The integrated methodology was applied to the data retrieved from nine weather stations in Taiwan. Our findings reveal rainstorm characteristics of "short D but high rainfall intensity" or "lower MAXI but high TR" across multiple stations. The parabolic trend of the first-order moment (i.e., mean) of ARI, D, and TR appears at the endpoint of the mountain ranges. Areas receiving monsoons and those on the windward plain show a rising parabolic trend in the first- and second-order moments (i.e., mean-variance) characterizing MAXI, implying that the occurrence frequency and magnitude of extreme MAXI increases. Non-stationary transitions in MAXI appear for mountain ranges exposed to the monsoon co-movement effect on both windward and leeward sides. Stations in the plains and rift valleys show upgraded and downgraded transitions in the non-stationary dimensions for D, respectively.

The association between childhood adiposity in northeast China and anthropogenic heat flux: A new insight into the comprehensive impact of human activities

Anthropogenic heat has been reported to have significant health impacts, but research on its association with childhood adiposity is still lacking. In this study, we matched the 2008-2012 average anthropogenic heat flux, as simulated by a grid estimation model using inventory methods, with questionnaire and measurement data of 49,938 children randomly recruited from seven cities in Northeast China in 2012. After adjusting for social demographic and behavioral factors, we used generalized linear mixed-effect models to assess the association between anthropogenic heat flux and adiposity among children. We also examined the effect modification of various social demographic and behavioral confounders. We found that each 10 W/m2 increase in total anthropogenic heat flux and that from the industry source was associated with an increase of 5.82% (95% CI = 0.84%-11.05%) and 6.62% (95% CI = 0.87%-12.70%) in the odds of childhood adiposity. Similarly, the excess rate of adiposity among children were 5.26% (95% CI = -1.33%-12.29%) and 8.51% (95% CI = 2.24%-15.17%) per 1 W/m2 increase in the anthropogenic heat flux from transportation and buildings, and was 7.94% (95% CI = 2.28%-13.91%) per 0.001 W/m2 increase in the anthropogenic heat flux from human metabolism. We also found generally greater effect estimates among female children and children who were exposed to passive smoking during pregnancy, born by caesarean section, non-breastfed/mixed-fed, or lived within 20 m adjacent to the main road. The potential deleterious effect of anthropogenic heat exposure on adiposity among children may make it a new but major threat to be targeted by future mitigation strategies.