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.     

Assessment of Metal Pollution in Water and Surface Sediments of the Seyhan River,Turkey, Using Different Indexes

The aim of this study was to assess the level of heavy metals (Al, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn) contamination and enrichment in the surface sediments of the Seyhan River, which is the receiving water body of both treated and untreated municipal and industrial effluents as well as agricultural drainage waters generated within Adana, Turkey. Sediment and water samples were taken from six previously determined stations covering the downstream of the Seyhan dam during both wet and dry seasons and the samples were then analyzed for the heavy metals of concern. When both dry and wet seasons were considered, metal concentrations varied significantly within a broad range with Al, 7210–33 967 mg kg^?1 dw; Cr, 46–122 mg kg^?1 dw; Cu, 6–57 mg kg^?1 dw; Fe, 10 294–26 556 mg kg^?1 dw; Mn, 144–638 mg kg^?1 dw; Ni, 82–215 mg kg^?1 dw; Pb, 11–75 mg kg^?1 dw; Zn, 34–146 mg kg^?1 dw in the sediments while Cd was at non‐detectable levels for all stations. For both seasons combined, the enrichment factor (EF) and the geo‐accumulation index (I_geo) for the sediments in terms of the specified metals ranged from 0.56 to 10.36 and ?2.92 to 1.56, respectively, throughout the lower Seyhan River. The sediment quality guidelines (SQG) of US‐EPA suggested the sediments of the Seyhan River demonstrated “unpolluted to moderate pollution” of Cu, Pb, and Zn, “moderate to very strong pollution” of Cr and Ni. The water quality data, on the other hand, indicated very low levels of these metals suggesting that the metal content in the surface sediments were most probably originating from fine sediments transported along the river route instead of water/wastewater discharges with high metal content.     

Creation of Histograms for Data in Various Mineral Resource and Engineering Problems: A Review of Existing Methods and a Proposed New Method to Define Bin Number

Histograms are widely used in geosciences for data analysis and visualization. In cases where a distribution is not fitted to data, histograms are often used to address various sampling- and interpolation-related aspects. However, the results of these applications are substantially affected by the histogram’s number of bins as determined by several binning methods. This paper proposes a new binning approach and compares it with various standard approaches to demonstrate the relative performance of the new approach. Cut-off grade optimization for polymetallic deposits, Monte-Carlo modeling, and derivation of conditional distribution, all of which use histograms, are used as case studies. The proposed technique is based on calculating the squared error for each bin in a histogram, and combining the error values to evaluate the total error for each histogram. The new technique then selects the bin number which minimizes the total error. The results showed that the new binning approach is well suited for binning small datasets and can be used in geoscience applications if needed.     

The interannual precipitation variability in the southern part of Iran as linked to large-scale climate modes

The interannual variation of precipitation in the southern part of Iran and its link with the large-scale climate modes are examined using monthly data from 183 meteorological stations during 1974–2005. The majority of precipitation occurs during the rainy season from October to May. The interannual variation in fall and early winter during the first part of the rainy season shows apparently a significant positive correlation with the Indian Ocean Dipole (IOD) and El Ni?o-Southern Oscillation (ENSO). However, a partial correlation analysis used to extract the respective influence of IOD and ENSO shows a significant positive correlation only with the IOD and not with ENSO. The southeasterly moisture flux anomaly over the Arabian Sea turns anti-cyclonically and transport more moisture to the southern part of Iran from the Arabian Sea, the Red Sea, and the Persian Gulf during the positive IOD. On the other hand, the moisture flux has northerly anomaly over Iran during the negative IOD, which results in reduced moisture supply from the south. During the latter part of the rainy season in late winter and spring, the interannual variation of precipitation is more strongly influenced by modes of variability over the Mediterranean Sea. The induced large-scale atmospheric circulation anomaly controls moisture supply from the Red Sea and the Persian Gulf.     

Long-term trends of seasonal dusty day characteristics—West Iran

In order to examine the seasonal characteristics of the dust events over western parts of Iran, surface observations from 27 meteorological stations for the period 1951–2014 were analyzed to obtain spatial distributions and temporal variations and trend of dusty day frequency (DDF). Trends of DDF were analyzed by Mann–Kendall and Sen’s estimator of slope nonparametric statistics. Three meteorological stations were selected in north (Tabriz), middle (Kermanshah), and south of the study area (Ahwaz) as reference stations for detecting the regional differences of DDFs. The results showed that DDF is a variable season by season but in general, DDF increases from north to south and from east to west of Iran. The maximum of DDF is monitored in May, June, and July. There are tangible seasonal increasing–decreasing periods in which these changes are logically related with seasonal changes. Regardless of the existence of the maximum DDF in south and southwest of study area, the most intensive increasing DDF trend is calculated in west middle areas. The most widespread and intensive increasing DDF pattern in west of Iran is observed when it is spring. In this case, the dust storms replaced the rainfalls. Distance from dust sources, major movement ways of dust transporting synoptic systems, regional effective wind activity (such as Shamal wind), and arrangement of high mountains are the known factors affecting frequency variation, distribution, and rate of the trend of all the dust phenomena in west of Iran.     

Application of the finite element method to gravity data case study: Western Turkey

Gravity anomalies always include the total effects (combination of the structures which have different densities and depths) of the study area and beyond. And the well-known non-uniqueness of potential field modelling may lead to very different interpretation results.The finite element method (FEM), which has been used in potential field interpretation for decades, makes complex problems to be solved easily and accurately. The first step of FEM is to identify the elements and then to decide on the boundary of the solution space. In this step, the solution space is divided into elements. After determination of the geometrical structure of the solution space, the most suitable elements should be chosen for this geometrical structure. The agreement between the geometry and the elements is quite important for the convergence to the best possible solution.In this work, the methods of trend analysis, filtering, analytical continuation and FEM were applied to a theoretical model and to gravity data from western Turkey to produce the regional and the residual anomalies. The results were compared and it was found that the FEM produced more accurate results than other methods did.     

Environmental determinants of littoral paludification in boreal lakes

Numerical studies of the relationships between littoral processes and environmental variables are important because they provide understanding of the impacts of natural and human factors on lake systems. In this study, littoral paludification, its occurrence, types and main environmental determinants were studied in boreal lakes with varying size (41–560 km²) and total phosphorus content (4.5–35.5 μg L⁻¹) in Finland. The relative importance of catchment characteristics, water quality and water level regulation on paludification was analysed at the lake level (n=20), whereas the importance of site morphology, soil quality and aquatic vegetation was analysed at the site level (n=289). This study utilised two novel statistical methods in numerical analyses: generalised linear mixed models and variation partitioning (VP). Bottom ward overgrowth was the main paludification type in the studied lakes. At the lake level, the magnitude of spring flooding and the altitude of the lake had a negative response to paludification, whereas the existence of water level regulation, cover of clay soil and total phosphorus content correlated positively to paludification. At the site level, the paludification was negatively related to slope angle, and positively to the occurrence of clay soil, Glyceria maxima (reed sweet-grass) and the abundance of eutrophy indicator species. However, a considerable amount of variation in littoral paludification both at lake and site levels was accounted for by the joint effects of predictors and may thus be causally related to two or all three groups of predictors.