Multiscale Analysis of Hydrology in a Mountaintop Mine‐Impacted Watershed

In the Appalachian region of the eastern United States, mountaintop removal mining (MTM) is a dominant driver of land‐cover change, impacting 6.8% of the largely forested 4.86 million ha coal fields region. Recent catastrophic flooding and documented biological impairment downstream of MTM has drawn sharp criticism to this practice. Despite its extent, scale, and use since the 1970s, the impact of MTM on hydrology is poorly understood. Therefore, the goal of this study was a multiscale evaluation to establish the nature of hydrologic impacts associated with MTM. To quantify the extent of MTM, land‐cover change over the lifetime of this practice is estimated for a mesoscale watershed in southern West Virginia. To assess hydrologic impacts, we conducted long‐term trend analyses to evaluate for systematic changes in hydrology at the mesoscale, and conducted hydrometric and response time modeling to characterize storm‐scale responses of a MTM‐impacted headwater catchment. Results show a general trend in the conversion of forests to mines, and significant decreases in maximum streamflow and variability, and increases in base‐flow ratio attributed to valley fills and deep mine drainage. Decreases in variability are shown across spatial and temporal scales having important implications for water quantity and quality. However, considerable research is necessary to understand how MTM impacts hydrology. In an effort to inform future research, we identify existing knowledge gaps and limitations of our study.     

When do you procrastinate? Sleep quality and social sleep lag jointly predict self‐regulatory failure at work

This study investigates antecedents of procrastination, the tendency to delay the initiation or completion of work activities. We examine this phenomenon from a self‐regulation perspective and argue that depleted self‐regulatory resources are an important pathway to explain why and when employees procrastinate. The restoration of self‐regulatory resources during episodes of non‐work is a prerequisite for the ability to initiate action at work. As sleep offers the opportunity to replenish self‐regulatory resources, employees should procrastinate more after nights with low‐quality sleep and shorter sleep duration. We further propose that people's social sleep lag amplifies this relationship. Social sleep lag arises if individuals' preference for sleep and wake times, known as their chronotype, is misaligned with their work schedule. Over five consecutive workdays, 154 participants completed a diary study comprising online questionnaires. Multilevel analyses showed that employees procrastinated less on days when they had slept better. The more employees suffered from social sleep lag, the more they procrastinated when sleep quality was low. Day‐specific sleep duration, by contrast, was not related to procrastination. We discuss the role of sleep for procrastination in the short run and relate our findings to research highlighting the role of sleep for well‐being in the long run. Copyright © 2016 John Wiley & Sons, Ltd.     

Development of numerical model for predicting heat generation and temperatures in MSW landfills

A numerical modeling approach has been developed for predicting temperatures in municipal solid waste landfills. Model formulation and details of boundary conditions are described. Model performance was evaluated using field data from a landfill in Michigan, USA. The numerical approach was based on finite element analysis incorporating transient conductive heat transfer. Heat generation functions representing decomposition of wastes were empirically developed and incorporated to the formulation. Thermal properties of materials were determined using experimental testing, field observations, and data reported in literature. The boundary conditions consisted of seasonal temperature cycles at the ground surface and constant temperatures at the far-field boundary. Heat generation functions were developed sequentially using varying degrees of conceptual complexity in modeling. First a step-function was developed to represent initial (aerobic) and residual (anaerobic) conditions. Second, an exponential growth-decay function was established. Third, the function was scaled for temperature dependency. Finally, an energy-expended function was developed to simulate heat generation with waste age as a function of temperature. Results are presented and compared to field data for the temperature-dependent growth-decay functions. The formulations developed can be used for prediction of temperatures within various components of landfill systems (liner, waste mass, cover, and surrounding subgrade), determination of frost depths, and determination of heat gain due to decomposition of wastes.     

Clustering species using a model of population dynamics and aggregation theory

The high species diversity of some ecosystems like tropical rainforests goes in pair with the scarcity of data for most species. This hinders the development of models that require enough data for fitting. The solution commonly adopted by modellers consists in grouping species to form more sizeable data sets. Classical methods for grouping species such as hierarchical cluster analysis do not take account of the variability of the species characteristics used for clustering. In this study a clustering method based on aggregation theory is presented. It takes account of the variability of species characteristics by searching for the grouping that minimizes the quadratic error (square bias plus variance) of some model’s prediction. This method allows one to check whether the gain in variance brought by data pooling compensate for the bias that it introduces. This method was applied to a data set on 94 tree species in a tropical rainforest in French Guiana, using a Usher matrix model to predict species dynamics. An optimal trade-off between bias and variance was found when grouping species. Grouping species appeared to decrease the quadratic error, except when the number of groups was very small. This clustering method yielded species groups similar to those of the hierarchical cluster analysis using Ward’s method when variance was small, that is when the number of groups was small.     

Spatial distribution of lindane in topsoil of Northern France

Lindane is a persistent organochlorine insecticide and the use of this insecticide in agriculture was banned in France in 1998. In this study we investigated the concentrations of lindane in topsoil in Northern France and used robust geostatistics to map the geographical distribution of lindane. The study was based on a 16 km × 16 km grid covering an area of ca 25 000 km². Lindane was found in all soils, even those from non-agricultural-application areas. Very low ratios of α-/γ-HCH and δ-/γ-HCH suggested that a long time had passed since technical HCH was used in the studied area, or that emission sources of lindane were still present. A strong gradient in lindane concentration was observed, with the highest lindane concentrations in an area located in the northern region. Results suggested that some of the lindane observed in the high concentration area may have come from volatilization of old lindane applied to intensively cultivated areas, which was then transported by prevailing winds coming from the south-west and deposited in a densely inhabited depression.     

A land use regression model for predicting ambient concentrations of nitrogen dioxide in Hamilton, Ontario, Canada

This paper reports on the development of a land use regression (LUR) model for predicting the intraurban variation of traffic-related air pollution in Hamilton, Ontario, Canada, an industrial city at the western end of Lake Ontario. Although land use regression has been increasingly used to characterize exposure gradients within cities, research to date has yet to test whether this method can produce reliable estimates in an industrialized location. Ambient concentrations of nitrogen dioxide (NO2) were measured for a 2-week period in October 2002 at > 100 locations across the city and subsequently at 30 of these locations in May 2004 to assess seasonal effects. Predictor variables were derived for land use types, transportation, demography, and physical geography using geographic information systems. The LUR model explained 76% of the variation in NO2. Traffic density, proximity to a highway, and industrial land use were all positively correlated with NO2 concentrations, whereas open land use and distance from the lake were negatively correlated with NO2. Locations downwind of a major highway resulted in higher NO2 levels. Cross-validation of the results confirmed model stability over different seasons. Our findings demonstrate that land use regression can effectively predict NO2 variation at the intraurban scale in an industrial setting. Models predicting exposure within smaller areas may lead to improved detection of health effects in epidemiologic studies.     

Monitoring the sonochemical degradation of phthalate esters in water using solid-phase microextraction

The sonochemical degradation of aqueous solutions containing low concentrations of six phthalate esters at an ultrasonic frequency of 80 kHz has been investigated. Ultrasonic treatment was found capable of removing the four higher molecular mass phthalates (di-n-butyl phthalate, butylbenzyl phthalate, di-(2-ethylhexyl) phthalate and di-n-octyl phthalate) within 30-60 min of irradiation. The rest (dimethyl phthalate and diethyl phthalate) were more recalcitrant and nearly complete removal could be achieved only after prolonged irradiation times. The relative reactivity of phthalates was explained in terms of their hydrophobicity. Experiments were carried out at an overall initial phthalate concentration of 240 microg l(-1), values of electric power of 75 and 150 W, temperatures of 21 and 50 degrees C and in the presence of NaCl to study the effect of various operating conditions on degradation. Solid-phase microextraction (SPME) coupled with GC-MS proved to be a powerful analytical tool to monitor the sonochemical degradation of phthalate esters at low microg l(-1) concentration levels, minimising the risk of secondary contamination during sample preparation, a major parameter to consider during phthalates analysis. The advantages as well as disadvantages of using SPME are also highlighted.     

Effect of dissolved oxygen concentration on nitrite accumulation in nitrifying sequencing batch reactor.

A mathematical model based on Activated Sludge Model No. 3 (International Water Association, London) and laboratory-scale experiments were used to investigate ammonia conversion by nitrification in a sequencing batch reactor (SBR). The purpose of the study was to assess the effect of dissolved oxygen concentration on nitrite accumulation in the SBR. As the dissolved oxygen concentration in the SBR depends on the balance between oxygen consumption and oxygen transfer rates, ammonium conversion was measured for different air flowrate values to obtain different dissolved oxygen concentration profiles during the cycle. The ammonia concentration in the feeding medium was 500 mg ammonium as nitrogen (N-NH4(+))/L, and the maximum nitrite concentration achieved during a cycle was approximately 50 mg nitrite as nitrogen (N-NO2)/L. The air flow supplied to the reactor was identified as a suitable parameter to control nitrite accumulation in the SBR. This identification was carried out based on experimental results and simulation with a calibrated model. At a low value of the volumetric mass-transfer coefficient (kLa), the maximum nitrite concentration achieved during a cycle depends strongly on k(L)a, whereas, at a high value of k(L)a, the maximum nitrite concentration was practically independent of kL(a).     

Predominant anthropogenic sources and rates of atmospheric mercury accumulation in southern Ontario recorded by peat cores from three bogs: comparison with natural "background" values (past 8000 years)

Peat cores from three bogs in southern Ontario provide a complete, quantitative record of net rates of atmospheric Hg accumulation since pre-industrial times. For comparison with modern values, a peat core extending back 8000 years was used to quantify the natural variations in Hg fluxes for this region, and their dependence on climatic change and land use history. The net mercury accumulation rates were separated into "natural" and "excess" components by comparing the Hg/Br ratios of modern samples with the long-term, pre-anthropogenic average Hg/Br. The average background mercury accumulation rate during the pre-anthropogenic period (from 5700 years BC to 1470 AD) was 1.4 +/- 1.0 microg m(-2) per year (n = 197). The beginning of Hg contamination from anthropogenic sources dates from AD 1475 at the Luther Bog, corresponding to biomass burning for agricultural activities by Native North Americans. During the late 17th and 18th centuries, deposition of anthropogenic Hg was at least equal to that of Hg from natural sources. Anthropogenic inputs of Hg to the bogs have dominated continuously since the beginning of the 19th century. The maximum Hg accumulation rates decrease in the order Sifton Bog, in the City of London, Ontario (141 microg Hg m(-2) per year), Luther Bog in an agricultural region (89 microg Hg m(-2) per year), and Spruce Bog which is in a comparatively remote, forested region (54 microg Hg m(-2) per year). Accurate age dating of recent peat samples using the bomb pulse curve of 14C shows that the maximum rate of atmospheric Hg accumulation occurred during AD 1956 and 1959 at all sites. In these (modern) samples, the Hg concentration profiles resemble those of Pb, an element which is known to be immobile in peat bogs. The correlation between these two metals, together with sulfur, suggests that the predominant anthropogenic source of Hg (and Pb) was coal burning. While Hg accumulation rates have gone into strong decline since the late 1950's, Hg deposition rates today still exceed the average natural background values by 7 to 13 times.