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.     

Mitigation Costs in a Globalized World: Climate Policy Analysis with REMIND-R

Within this paper, we present the novel hybrid model REMIND-R and its application in a climate policy context based on the EU target to avoid a warming of the Earth’s atmosphere by more than 2°C compared to the pre-industrial level. This paper aims to identify necessary long-term changes in the energy system and the magnitude of costs to attain such a climate protection target under different designs of the post-2012 climate policy regime. The regional specification of mitigation costs is analyzed in the context of globalization where regions are linked by global markets for emission permits, goods, and several resources. From simulation experiments with REMIND-R, it turns out that quite different strategies of restructuring the energy system are pursued by the regions. Furthermore, it is demonstrated that the variance of mitigation costs is higher across regions than across policy regimes. First-order impacts, in particular, reduced rents from trade in fossil resources, prevail regardless of the design of the policy regime.     

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.     

Long-term seasonal changes of the Danube River eco-chemical status in the region of Serbia

Seasonal spatial and temporal changes of selected eco-chemical parameters in section of the Danube River flowing through Serbia were analyzed. Data for electrical conductivity (EC), dry and suspended matter, residue on ignition, chemical oxygen demand (COD), biochemical oxygen demand (BOD-5), ultraviolet extinction, dissolved oxygen (DO), oxygen saturation, pH, nitrates, total phosphorus, and nitrogen were collected between 1992 and 2006. The use of monthly medians combined with linear regression and two-sided t test has been proven to be the best approach for resolving trends from natural variability of investigated parameters and for determining trend significance. Patterns of temporal changes between different months were examined. It was also determined that spatial trends of some parameters oscillate in predictable manner, increasing in one part of the year and declining in the other. Regression slope coefficients, an excellent indicator for determining when the water quality is changing the most along the course of the Danube, reach their maximum during summer for temperature (t), electric conductivity, nitrates, and total N, while in the same season suspended matter, COD, BOD-5, DO, and oxygen saturation coefficients reach their minimum. Correlations for used data sets of selected parameters were analyzed for better understanding of their behavior and mutual relations. It was observed that as Danube flows through Serbia, its general eco-chemical status either stagnates or improves, but the rate of river self-purification often depends on the season of the year.     

Fish scales as indicators of wastewater toxicity from an international water channel Tung Dhab drain

The effect of wastewater exposure on scales and chromatophores of freshwater fish Channa punctatus was studied using wastewater dilutions (60–100%) from an international water channel Tung Dhab drain at an interval of 15 and 30 days. The exposed fish showed significant alterations such as uprooted and damaged lepidonts and dispersal of chromatophores. These observations strongly suggest that fish scales can be successfully employed as indicators of wastewater pollution.     

Groundwater contamination evolution in the Guadiamar and Agrio aquifers after the Aznalcóllar spill: assessment and environmental implications

In 1998, the Agrio and Guadiamar rivers underwent an enormous environmental disaster caused by the rupture of the Aznalcóllar tailings dam and the release of 6 hm³ of pyrite sludge and acidic water. Both rivers run over recent alluvial materials which form a small-sized aquifer which is however important because underground water feeds the flow of the rivers. This work analyzes the state of groundwater 10 years after the spill. Before the dam failure, this aquifer was already contaminated in the zone nearest to the mine, to which the impact of the spill was added. Contamination levels in the alluvial aquifer of the Agrio River have decreased remarkably. However, they are still important, with acidic pH values and high concentrations of toxic elements (maximum values of 16 mg/L of Zn and 15 mg/L of Al). There are also important levels of contamination in the Guadiamar alluvial area closest to the mine, as well as in specific zones located further south. The concentration of toxic elements is mainly controlled by pH. The evolution of contaminant levels show a sharp decrease after the first years following the spill, followed by a subsequent stabilization. It is necessary to take measures for the recovery of the aquifer because, otherwise, groundwater will continue contributing contaminants into the Agrio and Guadiamar rivers.     

Development of geomorphologic instantaneous unit hydrograph for a large watershed

Hill torrents cause a lot of environmental and property damage in Pakistan every year. Proper assessment of direct runoff in the form of hill torrents is essential for protection of environment, property, and human life. In this paper, direct surface runoff hydrograph (DSRH) was derived for a large catchment using the geomorphologic instantaneous unit hydrograph concept. The catchment with hill torrent flows in semi-arid region of Pakistan was selected for this study. It was divided into series of linear cascades and hydrologic parameters required for Nash's conceptual model, and were estimated using geomorphology of the basin. Geomorphologic parameters were derived from satellite images of the basin and ERDAS and ArcGIS were used for data processing. Computer program was developed to systematically estimate the dynamic velocity, its related parameters by optimization and thereby to simulate the DSRH. The data regarding rainfall-runoff and satellite images were collected from Punjab Irrigation and Power Department, Pakistan. Model calibration and validation was made for 15 rainfall-runoff events. Ten events were used for calibration and five for validation. Model efficiency was found to be more than 90% and root mean square error to be about 5%. Impact of variation in model parameters (shape parameter and storage coefficient) on DSRH was investigated. For shape parameter, the number of linear cascades varied from 1 to 3 and it was found that the shaper parameter value of 3 produced the best DSRH. Various values of storage coefficient were used and it was observed that the value determined from geomorphology and the dynamic velocity produced the best results.     

A survey on the utility of the USEPA CADDIS stressor identification procedure

The Environmental Protection Agency (EPA) has made available on the worldwide web a systematic stream stressor identification procedure, the “Causal Analysis/Diagnosis Decision Information System” or CADDIS. We report here the results of a survey of regulators and scientists in 11 states who use CADDIS or another stressor identification procedure in their work. The 13 survey questions address guidelines as to what impairment scenarios to approach with stressor identification, what information is needed to perform stressor identification, and what the stakeholder role is in performing stressor identification. At the time of this survey (the summer of 2009), the EPA CADDIS website was less commonly used among the state regulators surveyed than the published EPA stressor identification document on which it is based. The respondents generally find the EPA stressor identification procedure useful and capable of being adapted to their individual needs. Survey respondents all use stressor identification in their Total Maximum Daily Load work, but also in a wide variety of other applications. All the “types of evidence” included in the CADDIS stressor identification procedure are used by the practitioners surveyed with the exception of the results of ecological simulation models. While the CADDIS documentation encourages the involvement of stakeholders in stressor identification, most respondents do not assemble stakeholder teams of local officials and citizens to participate in stressor analyses.     

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.