Types of narrow-skulled vole (<Emphasis Type="Italic">Lasiopodomys gregalis</Emphasis>) colonies in Northern Kulunda and seasonal dynamics of their demographic composition

Demographic structure and its seasonal dynamics have been studied in colonies of narrow-skulled voles (Lasiopodomys gregalis Pall.) in Northern Kulunda. Three types of colonies have been distinguished: (I) true colonies (large, complex families), (II) simple families (nuclear or incomplete), and (III) all-male colonies. Changes in their sex, age, and functional composition (based on animal migration activity) during the breeding season have been analyzed.     

Larch forests of Middle Siberia: long-term trends in fire return intervals

Fire history within the northern larch forests of Central Siberia was studied (65 + °N). Fires within this area are predominantly caused by lightning strikes rather than human activity. Mean fire return intervals (FRIs) were found to be 112 ± 49 years (based on firescars) and 106 ± 36 years (based on firescars and tree natality dates). FRIs were increased with latitude increase and observed to be about 80 years at 64°N, about 200 years near the Arctic Circle and about 300 years nearby the northern range limit of larch stands (~71° + N). Northward FRIs increase correlated with incoming solar radiation (r = ?0.95). Post-Little Ice Age (LIA) warming (after 1850) caused approximately a doubling of fire events (in comparison with a similar period during LIA). The data obtained support a hypothesis of climate-induced fire frequency increase.     

Using air quality modeling to study source–receptor relationships between nitrogen oxides emissions and ozone exposures over the United States

Human exposure to ambient ozone (O₃) has been linked to a variety of adverse health effects. The ozone level at a location is contributed by local production, regional transport, and background ozone. This study combines detailed emission inventory, air quality modeling, and census data to investigate the source–receptor relationships between nitrogen oxides (NO_x) emissions and population exposure to ambient O₃ in 48 states over the continental United States. By removing NO_x emissions from each state one at a time, we calculate the change in O₃ exposures by examining the difference between the base and the sensitivity simulations. Based on the 49 simulations, we construct state-level and census region-level source–receptor matrices describing the relationships among these states/regions. We find that, for 43 receptor states, cumulative NO_x emissions from upwind states contribute more to O₃ exposures than the state's own emissions. In-state emissions are responsible for less than 15% of O₃ exposures in 90% of U.S. states. A state's NO_x emissions can influence 2 to 40 downwind states by at least a 0.1 ppbv change in population-averaged O₃ exposure. The results suggest that the U.S. generally needs a regional strategy to effectively reduce O₃ exposures. But the current regional emission control program in the U.S. is a cap-and-trade program that assumes the marginal damage of every ton of NO_x is equal. In this study, the average O₃ exposures caused by one ton of NO_x emissions ranges from ? 2.0 to 2.3 ppm-people-hours depending on the state. The actual damage caused by one ton of NO_x emissions varies considerably over space.     

Numerical simulation of an array of fences in Saemangeum reclaimed land

This paper discusses about the quantitative effect of windbreak fences on wind velocity in the reclaimed land at Saemangeum in South Korea. Windbreak fences were constructed in the reclaimed land to reduce the wind velocity to prevent the generation and diffusion of dust. However, up to this time, no in-depth studies were conducted to quantitatively measure the effect of the windbreak fences on wind velocity thus an optimum windbreak structure is not yet determined. Using CFD simulations, the effects of fence porosity, fence height, and the distance between the adjacent fences were investigated. A wind tunnel experiment was initially conducted and data gathered were used to develop the CFD models. From the experiments and CFD simulations, the overall percentage difference of the measured velocities was 7.20% which is generally acceptable to establishing the reliability of the CFD models. The reduction effect on wind velocity was measured in between the adjacent fences up to a height of 0.6 m from the ground surface. In terms of porosity ( = 0, 0.2, 0.4, 0.6), 0.2 was found to be the optimum value. Conversely, the effect of fence height (0.6, 0.8 and 1.0 m) showed no significant difference; therefore, 0.6 m height is recommended. In addition, the reduction effect of distance between the adjacent fences (2, 4 and 6 m) on wind velocity having a 0.2 porosity has decreased to about 75% regardless of the distance. In the case of the reclaimed land in Saemangeum, a decrease of 75% can prevent the generation and diffusion of dusts. However, the source of dusts is very large. Therefore, constructing an array of windbreak with 6 m distance between them is deemed necessary.     

Examining intra-urban variation in fine particle mass constituents using GIS and constrained factor analysis

Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM_2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO₂) and PM_2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM_2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM_2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

A computational study of particulate emissions from an open pit quarry under neutral atmospheric conditions

The extraction of minerals from surface mines and quarries can produce significant fugitive dust emissions as a result of site activities such as blasting, road haulage, loading, crushing and stockpiling. If uncontrolled, these emissions can present serious environmental, health, safety and operational issues impacting both site personnel and the wider community.The dispersion of pollutant emissions within the atmosphere is principally determined by the background wind systems characterized by the atmospheric boundary layer (ABL). This paper presents an overview of the construction and solution of a computational fluid dynamics (CFD) model to replicate the development of the internal ventilation regime within a surface quarry excavation due to the presence of a neutral ABL above this excavation. This model was then used to study the dispersion and deposition of fugitive mineral dust particles generated during rock blasting operations. The paths of the mineral particles were modelled using Lagrangian particle tracking. Particles of four size fractions were released from five blast locations for eight different wind directions.The study concluded that dependent on the location of the bench blast within the quarry and the direction of the wind, a mass fraction of between 0.3 and 0.6 of the emitted mineral particles was retained within the quarry. The retention was largest when the distance from the blast location to the downwind pit boundary was greatest.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

Loofa egyptiaca as a novel adsorbent for removal of direct blue dye from aqueous solution

In this paper, Loofa egyptiaca (LE), an agricultural plant cultivated in Egypt, was used to prepare low-cost activated carbon (LE_C1 and LE_C2) adsorbents. The adsorbents (LE, LE_C1 and LE_C2) were evaluated for their ability to remove direct blue 106 dye from aqueous solutions. Batch mode experiments were conducted using various parameters such as pH, contact time, dye concentration and adsorbent concentration. The surface chemistry of LE, LE_C1 and LE_C2 was analyzed by scanning electron microscopy (SEM). The experimental data were examined using Langmuir, Freundlich, Temkin and Harkins–Jura isotherms. The results showed that the adsorption of direct blue 106 was maximal at the lowest value of pH (pH = 2). Removal efficiency was increased with an increase in dye concentration and a decrease in amount of adsorbent. Maximum adsorption capacity was found to be 57.14, 63.3 and 73.53 mg/g for LE, LE_C1 and LE_C2 respectively. Kinetics were also investigated using pseudo-first-order, pseudo-second-order and intra-particle diffusion models. The experimental data fitted very well with the pseudo-first-order and pseudo-second-order kinetic models. The results indicate that LE, LE_C1 and LE_C2 could be employed as adsorbents for the removal of direct blue dye from aqueous solutions.