Environmental pollution is a global problem and the subject of increasing worldwide public health concern.1 In particular, air pollution is regarded as the largest single environmental risk to health. More than 80% of people living in urban areas that monitor air pollution are exposed to air quality levels that exceed the WHO limits, and all regions of the world are affected. Declines in urban air quality increase the risk of cerebrovascular accidents, coronary artery disease, lung carcinoma, and chronic and acute respiratory diseases (eg, asthma, obstructive lung disease, and acute lower respiratory infections).
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.
Climate forecasts predict an increase in frequency and intensity of wildfires. Associations between health outcomes and population exposure to smoke from Washington 2012 wildfires were compared using surface monitors, chemical-weather models, and a novel method blending three exposure information sources. The association between smoke particulate matter ≤2.5 μm in diameter (PM2.5) and cardiopulmonary hospital admissions occurring in Washington from 1 July to 31 October 2012 was evaluated using a time-stratified case-crossover design. Hospital admissions aggregated by ZIP code were linked with population-weighted daily average concentrations of smoke PM2.5 estimated using three distinct methods: a simulation with the Weather Research and Forecasting with Chemistry (WRF-Chem) model, a kriged interpolation of PM2.5 measurements from surface monitors, and a geographically weighted ridge regression (GWR) that blended inputs from WRF-Chem, satellite observations of aerosol optical depth, and kriged PM2.5. A 10 μg/m3 increase in GWR smoke PM2.5 was associated with an 8% increased risk in asthma-related hospital admissions (odds ratio (OR): 1.076, 95% confidence interval (CI): 1.019–1.136); other smoke estimation methods yielded similar results. However, point estimates for chronic obstructive pulmonary disease (COPD) differed by smoke PM2.5 exposure method: a 10 μg/m3 increase using GWR was significantly associated with increased risk of COPD (OR: 1.084, 95%CI: 1.026–1.145) and not significant using WRF-Chem (OR: 0.986, 95%CI: 0.931–1.045). The magnitude (OR) and uncertainty (95%CI) of associations between smoke PM2.5 and hospital admissions were dependent on estimation method used and outcome evaluated. Choice of smoke exposure estimation method used can impact the overall conclusion of the study.
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.