Future climate change is expected to lengthen and intensify pollen seasons in the U.S., potentially increasing incidence of allergic asthma. We developed a proof-of-concept approach for estimating asthma emergency department (ED) visits in the U.S. associated with present-day and climate-induced changes in oak pollen. We estimated oak pollen season length for moderate (Representative Concentration Pathway (RCP) 4.5) and severe climate change scenarios (RCP8.5) through 2090 using five climate models and published relationships between temperature, precipitation, and oak pollen season length. We calculated asthma ED visit counts associated with 1994–2010 average oak pollen concentrations and simulated future oak pollen season length changes using the Environmental Benefits Mapping and Analysis Program, driven by epidemiologically derived concentration-response relationships. Oak pollen was associated with 21,200 (95% confidence interval, 10,000–35,200) asthma ED visits in the Northeast, Southeast, and Midwest U.S. in 2010, with damages valued at $10.4 million. Nearly 70% of these occurred among children age <18 years. Severe climate change could increase oak pollen season length and associated asthma ED visits by 5% and 10% on average in 2050 and 2090, with a marginal net present value through 2090 of $10.4 million (additional to the baseline value of $346.2 million). Moderate versus severe climate change could avoid >50% of the additional oak pollen-related asthma ED visits in 2090. Despite several key uncertainties and limitations, these results suggest that aeroallergens pose a substantial U.S. public health burden, that climate change could increase U.S. allergic disease incidence, and that mitigating climate change may have benefits from avoided pollen-related health impacts.
As the global human population continues to grow, so too does our impact on the environment. The ingenuity with which our species has harnessed natural resources to fulfill our needs is dazzling. Even as we tighten our grip on the environment, however, the escalating extent of anthropogenic actions destabilizes long-standing ecological balances (1, 2). The dangers of mining, refining, and fossil fuel consumption now extend beyond occupational or proximate risks to global climate change (3). Among a plethora of environmental problems, extreme climate events are intensifying (4, 5). Storms, droughts, and floods cause direct destruction, but also have pervasive repercussions on food security, infectious disease transmission, and economic stability that take their toll for many years. For example, within weeks of the catastrophic wind and flood damage from the 2016 Hurricane Matthew in Haiti, there was a dramatic surge in cholera, among other devastating repercussions (6, 7). In a world where 1% of the population possesses 50% of the wealth (8), those worst affected by extreme climatic events and the aftermath are also the least able to rebound.
Severe smoke haze from biomass burning is frequently observed in Northern Thailand during dry months of February–April. Sparsely located monitoring stations operated in this vast mountainous region could not provide sufficient particulate matter (PM) data for exposure risk assessment. Satellite aerosol optical thickness (AOT) data could be used, but their reliable relationship with ground-based PM data should be first established. This study aimed to improve the regression model between PM10 and Moderate Resolution Imaging Spectroradiometer AOT with consideration of synoptic patterns to better assess the exposure risk in the area. Among four synoptic patterns, each representing the totality of meteorology governing Northern Thailand on a given day, most severe haze days belonged to pattern 2 that featured conditions of clear sky, stagnant air, and high PM10 levels. AOT-24 h PM10 regression model for pattern 2 had coefficient of determination improved to 0.51 from 0.39 of combined case. Daily exposure maps to PM10 in most severe haze period of February–April 2007 were produced for Chiangmai, the largest and most populated province in Northern Thailand. Regression model for pattern 2 was used to convert 24 h PM10 ranges of modified risk scale to corresponding AOT ranges, and the mapping was done using spatially continuous AOT values. The highest exposure risk to PM10 was shown in urban populated areas. Larger numbers of forest fire hot spots and more calm winds were observed on the days of higher exposure risk. Early warning and adequate health care plan are necessary to reduce exposure risk to future haze episodes in the area.
Few studies focus on environment in its biological dimension, relating territorial/landscape alteration and human health, beyond pollution impact. The growing importance of risk factors in medicine and the new ecological advancements in Landscape Bionomics impose to deepen these studies. The landscape is a living entity, in which man and territory form a complex biological level of life organization. So, a landscape must be investigated in its physiology and behaviour by the discipline of Landscape Bionomics. This to check “if”, “how” and “how much” landscape alterations could reflect on human health, independently form pollution. First evidences of a clear correlation subsist, concerning an increase of mortality rate within Milan hinterland (Italy). The Landscape dysfunctions are correlated with the increase of mortality rate MR. All the environmental alterations are registered as ‘stressors’ by a basilar ethological alarm process. So, bionomic landscape dysfunctions may attempt our health bringing to an excess of cortisol, which reduces our hormonal, immune and nervous system defences. This enlarges the W.H.O. estimation of the environmental MR and the importance of applications impose a true effort in landscape rehabilitation.
Understanding feedbacks between human and environmental health is critical for the millions who cope with recurrent illness and rely directly on natural resources for sustenance. Although studies have examined how environmental degradation exacerbates infectious disease, the effects of human health on our use of the environment remains unexplored. Human illness is often tacitly assumed to reduce human impacts on the environment. By this logic, ill people reduce the time and effort that they put into extractive livelihoods and, thereby, their impact on natural resources. We followed 303 households living on Lake Victoria, Kenya over four time points to examine how illness influenced fishing. Using fixed effect conditional logit models to control for individual-level and time-invariant factors, we analyzed the effect of illness on fishing effort and methods. Illness among individuals who listed fishing as their primary occupation affected their participation in fishing. However, among active fishers, we found limited evidence that illness reduced fishing effort. Instead, ill fishers shifted their fishing methods. When ill, fishers were more likely to use methods that were illegal, destructive, and concentrated in inshore areas but required less travel and energy. Ill fishers were also less likely to fish using legal methods that are physically demanding, require travel to deep waters, and are considered more sustainable. By altering the physical capacity and outlook of fishers, human illness shifted their effort, their engagement with natural resources, and the sustainability of their actions. These findings show a previously unexplored pathway through which poor human health may negatively impact the environment.
Contrary to widespread assumptions, next-generation high (annual to multi-annual) and ultra-high (sub-annual) resolution analysis of an Alpine glacier reveals that true historical minimum natural levels of lead in the atmosphere occurred only once in the last ca. 2000 years. During the Black Death pandemic, demographic and economic collapse interrupted metal production and atmospheric lead dropped to undetectable levels. This finding challenges current government and industry understanding of pre-industrial lead pollution and its potential implications for human health of children and adults worldwide. Available technology and geographic location have limited previous ice core investigations. We provide new high- (discrete, inductively coupled mass spectrometry, ICP-MS) and ultra-high resolution (laser ablation inductively coupled mass spectrometry, LA-ICP-MS) records of atmospheric lead deposition extracted from the high Alpine glacier Colle Gnifetti, in the Swiss-Italian Alps. We show that, contrary to the conventional wisdom, low levels at or approaching natural background occurred only in a single four-year period in the ca. 2000 years documented in the new ice core, during the Black Death (ca. 1349-1353 C.E.), the most devastating pandemic in Eurasian history. Ultra-high chronological resolution allows for the first time detailed and decisive comparison of the new glaciochemical data with historical records. Historical evidence shows that mining activity ceased upwind of the core site from ca. 1349 to 1353, while concurrently on the glacier lead (Pb) concentrations—dated by layer counting confirmed by radiocarbon dating—dropped to levels below detection, an order of magnitude beneath figures deemed low in earlier studies. Previous assumptions about pre-industrial “natural” background lead levels in the atmosphere—and potential impacts on humans—have been misleading, with significant implications for current environmental, industrial, and public health policy, as well as for the history of human lead exposure. Trans-disciplinary application of this new technology opens the door to new approaches to the anthropogenic impact on past and present human health. This article is protected by copyright. All rights reserved.