Working with Climate Projections to Estimate Disease Burden: Perspectives from Public Health

There is interest among agencies and public health practitioners in the United States (USA) to estimate the future burden of climate-related health outcomes. Calculating disease burden projections can be especially daunting, given the complexities of climate modeling and the multiple pathways by which climate influences public health. Interdisciplinary coordination between public health practitioners and climate scientists is necessary for scientifically derived estimates. We describe a unique partnership of state and regional climate scientists and public health practitioners assembled by the Florida Building Resilience Against Climate Effects (BRACE) program. We provide a background on climate modeling and projections that has been developed specifically for public health practitioners, describe methodologies for combining climate and health data to project disease burden, and demonstrate three examples of this process used in Florida

Effects of vibrational motion on core-level spectra of prototype organic molecules

A computational approach is presented for prediction and interpretation of core-level spectra of complex molecules. Applications are presented for several isolated organic molecules, sampling a range of chemical bonding and structural motifs. Comparison with gas phase measurements indicate that spectral lineshapes are accurately reproduced both above and below the ionization potential, without resort to ad hoc broadening. Agreement with experiment is significantly improved upon inclusion of vibrations via molecular dynamics sampling. We isolate and characterize spectral features due to particular electronic transitions enabled by vibrations, noting that even zero-point motion is sufficient in some cases

Evaluating the impact of urban morphology configurations on the accuracy of urban canopy model temperature simulations with MODIS

This is the author accepted manuscript. The published version can be found here: http://dx.doi.org/10.1002/2013JD021227.Simulations of the urban environment contribute to assessments of current and future urban vulnerabilities to extreme heat events. The accuracy of simulations of the urban canopy can be degraded by inaccurate or oversimplified representations of the urban-built environment within models. Using a 10 year (2003–2012) series of offline 1 km simulations over Greater Houston with the High-Resolution Land Data Assimilation System (HRLDAS), this study explores the model accuracy gained by progressively increasing the complexity of the urban morphology representation in an urban canopy model. The fidelity of the simulations is primarily assessed by a spatiotemporally consistent comparison of a newly developed HRLDAS radiative temperature variable with remotely sensed estimates of land surface temperature from the Moderate Resolution Imaging Spectroradiometer. The most accurate urban simulations of radiative temperature are yielded from experiments that (1) explicitly specify the urban fraction in each pixel and (2) include irrigation. The former modification yields a gain in accuracy that is larger than for other changes, such as increasing the number of urban land use types. The latter modification (irrigation) substantially reduces simulated temperature biases and increases model precision compared to model configurations that lack irrigation, presumably because watering of lawns, parks, etc. is a common activity that should be represented in urban canopy models (although it is generally not). Ongoing and future efforts to improve urban canopy model simulations may achieve important gains through better representations of urban morphology, as well as processes that affect near-surface energy partitioning within cities, such as irrigation.Funded by NASA. Grant Number: NNX10AK79

A ‘heart rate’-based model (PHSHR) for predicting personal heat stress in dynamic working environments

The parameter of human body metabolic rates has been popularly used for the prediction of human heat stress in hot environments. However, most modules use the fixed and estimated metabolic heat production. The aim of this study is to develop the prediction of personal heat stress in dynamic working environments. Based on the framework of the predicted heat stress (PHS) model in ISO 7933, a heart-rate based PHSHR model has been developed using the time-based heart rate index, which is suitable for prediction in situations where metabolic rates are dynamic and there are inter-individual variations. The infinitesimal time unit Δti, has been introduced into the new PHSHR model and all the terms used in the PHS model related to metabolic rates are thus redefined as the function of real-time heart rates. The PHSHR has been validated under 8 experimental combined temperature-humidity conditions in a well-controlled climate chamber. The feature of the PHSHR model is being able to calculate dynamic changes in body metabolism with exposure time. It will be useful to the identification of potential risks of individual workers so to establish an occupational working environment health and safety protection mechanism by means of simultaneous monitoring of workers’ heart rates at the personal levels, using advanced sensor technology

Environmental Predictors of Seasonal Influenza Epidemics across Temperate and Tropical Climates

Human influenza infections exhibit a strong seasonal cycle in temperate regions. Recent laboratory and epidemiological evidence suggests that low specific humidity conditions facilitate the airborne survival and transmission of the influenza virus in temperate regions, resulting in annual winter epidemics. However, this relationship is unlikely to account for the epidemiology of influenza in tropical and subtropical regions where epidemics often occur during the rainy season or transmit year-round without a well-defined season. We assessed the role of specific humidity and other local climatic variables on influenza virus seasonality by modeling epidemiological and climatic information from 78 study sites sampled globally. We substantiated that there are two types of environmental conditions associated with seasonal influenza epidemics: “cold-dry” and “humid-rainy”. For sites where monthly average specific humidity or temperature decreases below thresholds of approximately 11–12 g/kg and 18–21°C during the year, influenza activity peaks during the cold-dry season (i.e., winter) when specific humidity and temperature are at minimal levels. For sites where specific humidity and temperature do not decrease below these thresholds, seasonal influenza activity is more likely to peak in months when average precipitation totals are maximal and greater than 150 mm per month. These findings provide a simple climate-based model rooted in empirical data that accounts for the diversity of seasonal influenza patterns observed across temperate, subtropical and tropical climates

Soft X ray spectroscopy of light elements in energy storage materials

The increasing demand for electrochemical energy storage devices continuously promotes the development of new electrode materials and electrolytes. As a result, understanding their structural and electronic properties affecting electrochemical performance becomes crucial. The role of light elements, which are found in anode and cathode materials, in electrolytes and hence in the solid-electrolyte interphases, requires a special attention. Soft X-ray spectroscopies are particularly relevant to probe selectively light elements in complex environment. Here, the recent advances in the characterization of light elements in energy storage materials by soft X-ray spectroscopy and microscopy techniques are reviewed. After introducing the main X-ray spectroscopic methods and their application to ex situ/in situ/operando characterization of electrochemical processes, the role of light elements in the electrode for supercapacitors and Li/Na-ion storage applications is described. The characterization of electrolytes and related ion solvation is then briefly reviewed before describing how the formation and evolution of solid-electrolyte interphases can be monitored with these methods. Finally, major challenges and future opportunities for soft X-rays spectroscopy in the context of electrochemical energy storage are highlighted