The impact of extreme heat on morbidity in Milwaukee, Wisconsin

Given predictions of increased intensity and frequency of heat waves, it is important to study the effect of high temperatures on human mortality and morbidity. Many studies focus on heat wave-related mortality; however, heat-related morbidity is often overlooked. The goals of this study are to examine the historical observed relationship between temperature and morbidity (illness), and explore the extent to which observed historical relationships could be used to generate future projections of morbidity under climate change. We collected meteorological, air pollution, and hospital admissions data in Milwaukee, Wisconsin, for the years 1989–2005, and employed a generalized additive model (GAM) to quantify the relationship between morbidity (as measured by hospital admissions) and high temperatures with adjustment for the effects of potential confounders. We also estimated temperature threshold values for different causes of hospital admissions and then quantified the associated percent increase of admissions per degree above the threshold. Finally, the future impact of higher temperatures on admissions for the years 2059–2075 was examined. Our results show that five causes of admission (endocrine, genitourinary, renal, accidental, and self-harm) and three age groups (15–64, 75–84, >85 years) were affected by high temperatures. Future projections indicate a larger number of days above the current temperature threshold leading to an increase in admissions. Our results indicate that climate change may increase heat-related hospital admissions in the US urban mid-West and that health systems should include heat wave planning.     

The influence of dimensionality on simulations of mass recovery from nonuniform dense non-aqueous phase liquid (DNAPL) source zones

The influence of model dimensionality on predictions of mass recovery from dense non-aqueous phase liquid (DNAPL) source zones in nonuniform permeability fields was investigated using a modified version of the modular three-dimensional transport simulator (MT3DMS). Thirty-two initial two- (2D) and three-dimensional (3D) tetrachloroethene–DNAPL source zone architectures, taken from a recent modeling study, were used as initial conditions for this analysis. Commonly employed source zone metrics were analyzed to determine differences between 2D and 3D predictions: (i) down-gradient flux-averaged contaminant concentration, (ii) reductions in contaminant mass flux through a down-gradient boundary, (iii) source zone ganglia-to-pool (GTP) ratio, and (iv) time required to achieve a remediation objective. 3D flux-averaged contaminant concentrations were approximately 3.5 times lower than concentrations simulated in 2D. This difference was attributed to dilution of the contaminant concentrations down gradient of the source zone. Contaminant flux reduction predictions for a given mass recovery were generally 5% higher in 3D simulations than in 2D simulations. The GTP ratio declined over time as mass was recovered in both 2D and 3D simulations. Although the source longevity (i.e., time required to achieve 99.99% mass recovery) differed between individual 2D and 3D realizations, the mean source longevity for the 2D and 3D simulation ensembles was within 2%. 2D simulations tended to over-predict the time required to achieve lower mass recovery levels (e.g. 50% mass recovery) due to a smaller contaminated area exposed to uncontaminated water. These findings suggest that ensemble averages of 2D numerical simulations of DNAPL migration, entrapment, dissolution, and mass recovery in statistically homogenous, nonuniform media may provide reasonable approximations to average behavior obtained using simulations conducted in fully three-dimensional domains.