The occurrence of heavy metals in irrigated and non-irrigated arable soils,NW Albania

The study analysed the content of heavy metals in surface soil and sediment samples from the Bregu i Matit Plain in NW Albania in relation to irrigation in order to evaluate the soil pollution and the potential risk to human health. Evaluation of soil pollution was performed using the enrichment factor and geo-accumulation index. Contents of cadmium, chromium and nickel of irrigated soils were significantly higher than those of non-irrigated soil, while contents of lead (in three of the irrigated locations), zinc and arsenic (in one of the irrigated locations) were significantly lower. Correlation analysis (CA) and principal component analysis (PCA) indicated that the primary source of the first three metals was irrigation, and the last three metals were originated from other anthropic sources, like the use of chemicals, etc. Enrichment factor (E _f) calculation showed that irrigated soils were most enriched in cadmium, chromium, copper and nickel. Index of geo-accumulation (I _geo) revealed that arable soils of Bregu i Matit are unpolluted to moderately polluted with cadmium, chromium, copper and zinc and moderately to strongly polluted with nickel and arsenic. The presence of heavy metals in the studied soils indicates a potential risk of transfer of these elements in the food chain. Therefore, further studies on the speciation of heavy metals in the studied soils in order to evaluate their mobility are needed.     

Lead traceability along soil-melliferous flora-bee family-apiary products chain

Indirect measures were considered to study the lead transfer along the soil-melliferous flora-bee family-apiary products food chain. The concentrations of total and bioavailable lead in the soil were first investigated. Next, the lead level in different organs of melliferous flora and subsequently in the bee family and apiary products was measured. The results indicate a decrease in contamination as follows: honeybees > drones > propolis > wax > bee larvae > honey > royal jelly. The statistical analysis highlights the "lead pollution bioindicator" role of honeybees, honey and propolis. The risk factor parameter allows the prediction of the most impacted month and the least impacted of the melliferous season.     

Mapping afforestation and deforestation from 1974 to 2012 using Landsat time-series stacks in Yulin District, a key region of the Three-North Shelter region, China

The Three-North Shelter Forest Program is the largest afforestation reconstruction project in the world. Remote sensing is a crucial tool to map land use and land cover change, but it is still challenging to accurately quantify the change in forest extent from time-series satellite images. In this paper, 30 Landsat MSS/TM/ETM+ epochs from 1974 to 2012 were collected, and the high-quality ground surface reflectance (GSR) time-series images were processed by integrating the 6S atmosphere transfer model and a relative reflectance normalization algorithm. Subsequently, we developed a vegetation change tracking method to reconstruct the forest change history (afforestation and deforestation) from the time-series Landsat GSR images based on the integrated forest z-score (IFZ) model by Huang et al. (2009a), which was improved by multi-phenological IFZ models and the smoothing processing of IFZ data for afforestation mapping. The mapping result showed a large increase in the extent of forest, from 380,394 ha (14.8 % of total district area) in 1974 to 1,128,380 ha (43.9 %) in 2010. Finally, the land cover and forest change map was validated with an overall accuracy of 89.1 % and a kappa coefficient of 0.858. The forest change time was also successfully retrieved, with 22.2 % and 86.5 % of the change pixels attributed to the correct epoch and within three epochs, respectively. The results confirmed a great achievement of the ecological revegetation projects in Yulin district over the last 40 years and also illustrated the potential of the time-series of Landsat images for detecting forest changes and estimating tree age for the artificial forest in a semi-arid zone strongly influenced by human activities.     

Workplace aerosol mass concentration measurement using optical particle counters

Direct-reading aerosol measurement usually uses the optical properties of airborne particles to detect and measure particle concentration. In the case of occupational hygiene, mass concentration measurement is often required. Two aerosol monitoring methods are based on the principle of light scattering: optical particle counting (OPC) and photometry. The former analyses the light scattered by a single particle, the latter by a cloud of particles. Both methods need calibration to transform the quantity of scattered light detected into particle concentration. Photometers are simpler to use and can be directly calibrated to measure mass concentration. However, their response varies not only with aerosol concentration but also with particle size distribution, which frequently contributes to biased measurement. Optical particle counters directly measure the particle number concentration and particle size that allows assessment of the particle mass provided the particles are spherical and of known density. An integrating algorithm is used to calculate the mass concentration of any conventional health-related aerosol fraction. The concentrations calculated thus have been compared with simultaneous measurements by conventional gravimetric sampling to check the possibility of field OPC calibration with real workplace aerosols with a view to further monitoring particle mass concentration. Aerosol concentrations were measured in the food industry using the OPC GRIMM? 1.108 and the CIP 10-Inhalable and CIP 10-Respirable (ARELCO?) aerosol samplers while meat sausages were being brushed and coated with calcium carbonate. Previously, the original OPC inlet had been adapted to sample inhalable aerosol. A mixed aerosol of calcium carbonate and fungi spores was present in the workplace. The OPC particle-size distribution and an estimated average particle density of both aerosol components were used to calculate the mass concentration. The inhalable and respirable aerosol fractions calculated from the OPC data are closely correlated with the results of the particle size-selective sampling using the CIP 10. Furthermore, the OPC data allow calculation of the thoracic fraction of workplace aerosol (not measured by sampling), which is interesting in the presence of allergenic particles like fungi spores. The results also show that the modified COP inlet adequately samples inhalable aerosol in the range of workplace particle-size distribution.     

Selecting Variables for Habitat Suitability of <Emphasis Type="Italic">Asellus</Emphasis> (Crustacea,Isopoda) by Applying Input Variable Contribution Methods to Artificial Neural Network Models

This study aimed to compare different methods to analyse the contribution of individual river characteristics to predict the abundance of Asellus (Crustacea, Isopoda). Six methods which provide the relative contribution and/or the contribution profile of the input variables of artificial neural network models were therefore compared: (1) the ‘partial derivatives’ method; (2) the ‘weights’ method; (3) the ‘perturb’ method; (4) the ‘profile’ method; (5) the ‘classical stepwise’ method; (6) the ‘improved stepwise’ method. Consequently, the key variables which affect the habitat preferences of Asellus could be identified. To evaluate the performance of the artificial neural network model, the model predictions were compared with the results of a multiple linear regression analysis. The dataset consisted of 179 samples, collected over a 3-year period in the Zwalm catchment in Flanders, Belgium. Twenty-four environmental variables as well as the log-transformed abundance of Asellus were used in this study. The different contribution methods seemed to give similar results concerning the order of importance of the input variables. Nevertheless, their diverse computation led to differences in sensitivity and stability of the methods and the derived outcomes on the habitat preferences. From an ecological point of view, the environmental variables describing the stream type (width, depth, stream order and distance to mouth) were the most significant variables for Asellus in the Zwalm catchment during the period 2000–2002 for all applied methods. Indirectly, one can conclude that the water quality is not the limiting factor for the survival of Asellus in the Zwalm catchment.     

Sustainable Use of Coffee Husks For Reinforcing Polyethylene Composites

The utilization of the coffee husk fiber (CHF) from the coffee industry as a reinforcing filler in the preparation of a cost-effective thermoplastic based composite was explored in this study. The chemical composition and thermal properties of the CHF were investigated and compared with those of wood fiber (WF). CHF proved to be mainly composed of cellulose, hemicellulose and lignin, and exhibited similar thermal behavior to WF. High density polyethylene (HDPE) composites with CHF loadings of from 40 to 70% were prepared using melt processing and extrusion. The processing properties, mechanical behavior, water absorption and thermal performance of these composites were investigated. The effect of maleated polyethylene (MAPE) used as a coupling agent on the composite was explored. The experimental results showed that increasing the CHF loading in the HDPE matrix resulted in an increase in the modulus and thermal properties of the composites, but resulted in poor water resistance. The addition of a 4% MAPE significantly improved the interfacial behavior of the hydrophilic lignocellulosic fiber and the hydrophobic polymer matrix.     

Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem)

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM₁₀ observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM₁₀]).Furthermore, the model underestimated [PM₁₀] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model’s erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM₁₀] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model’s performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM₁₀] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM₁₀] in that region. Both 24-hr and 1-hr measured [PM₁₀] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM₁₀], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for.

Implications: While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered “natural”; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.