Bioremediation treatment of hydrocarbon-contaminated Arctic soils: influencing parameters

The Arctic environment is very vulnerable and sensitive to hydrocarbon pollutants. Soil bioremediation is attracting interest as a promising and cost-effective clean-up and soil decontamination technology in the Arctic regions. However, remoteness, lack of appropriate infrastructure, the harsh climatic conditions in the Arctic and some physical and chemical properties of Arctic soils may reduce the performance and limit the application of this technology. Therefore, understanding the weaknesses and bottlenecks in the treatment plans, identifying their associated hazards, and providing precautionary measures are essential to improve the overall efficiency and performance of a bioremediation strategy. The aim of this paper is to review the bioremediation techniques and strategies using microorganisms for treatment of hydrocarbon-contaminated Arctic soils. It takes account of Arctic operational conditions and discusses the factors influencing the performance of a bioremediation treatment plan. Preliminary hazard analysis is used as a technique to identify and assess the hazards that threaten the reliability and maintainability of a bioremediation treatment technology. Some key parameters with regard to the feasibility of the suggested preventive/corrective measures are described as well.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

Spatial variability of soil <Superscript>137</Superscript>Cs in the South Caspian region

In a comprehensive program of environmental radioactivity survey in South Caspian region,¹³⁷Cs inventories in soil has been measured at more than 50 sites in the Iranian northern province of Guilan. This has been the first wide-range survey of soil radionuclide inventories in the narrow band sensitive ecosystem of south Caspian shore. Radioactivity measurements were carried out using HPGe gamma-spectrometry system. The activity concentration of ¹³⁷Cs in surface soil exhibits a mean value of 17.6 ± 9.4 Bq kg⁻¹, with a range of 2.3–41.7 Bq kg⁻¹. In many sites, split-level sampling method has been applied down to a depth of 20 cm. There were found generally two profiles. Most profiles exhibit a negative exponential distribution, while others revealed a clear subsurface peak in 5–10-cm layer. Cesium deposition in the study area has been estimated to be in the range of 0.38–2.9 kBq m⁻² with a mean value of 1.7 kBq m⁻². Distribution patterns of ¹³⁷Cs concentration levels and deposition values have been estimated using Kriging interpolation method. Observed hotspots in deposition pattern coincide with areas of higher precipitation.     

Examination of compensatory model application in site selection

Nowadays, usage of compensatory models in land evaluation process and site selection is broadly observed. Meanwhile, methods such as analytical hierarchy process are used more than the others. Whether the usage of compensatory model methods in site selection studies is essentially correct or not is an issue that should be hesitated. In this model, inefficiency of a factor, to be offset by strength of others, means that in urban development site selection, if somewhere has unsuitable aspect but suitable slope, the aspect deficiency will be compensated by the slope. But quodlibet reflection is that in this model, sometimes, deficiency of proximity to fault can be compensated by other parameters strength. And finally, a place is diagnosed as a suitable area for urban development that is close to the fault. This research aims at examination of compensatory models application in urban development site selection of Taleghan Basin using analytical hierarchy process as one of the compensatory model methods. Among this the weaknesses and strengths of compensatory model were analyzed carefully. Results indicate that despite usefulness of this model in being fast, easy, and low expense, it has some weaknesses like very high sensitivity to decision maker’s idea.     

Evaluation of the use of diffusive air samplers for determining temporal and spatial variation of volatile organic compounds in the ambient air of urban communities

The Houston-Galveston metropolitan area has a relatively high density of point and mobile sources of air toxics, and determining and understanding the relationship between emissions and ambient air concentrations of air toxics is important for evaluating potential impacts on public health and formulating effective regulatory policies to control this impact, both in this region and elsewhere. However, conventional ambient air monitoring approaches are limited with regard to expense, siting limitations, and representative sampling necessary for adequate exposure assessment. The overall goal of this multiphase study is to evaluate the use of simple passive air samplers to determine temporal and spatial variability of the ambient air concentrations of selected volatile organic compounds (VOCs) in urban areas. Phase 1 of this study, reported here, was a field evaluation of 3M organic vapor monitors (OVMs) involving limited comparisons with commonly used active sampling methods, an assessment of sampler precision, a determination of optimal sampling duration, and an investigation of the utility of a simple modification of the commercial sampler. The results indicated that a sampling duration of 72 hr exhibited generally low bias relative to automated continuous gas chromatography measurements, good overall precision, and an acceptable number of measurements above detection limits. The modified sampler showed good correlation with the commercial sampler, with higher sampling rates, although lower than expected.     

Design of River Water Quality Monitoring Networks: A Case Study

Karoon River, from Gotvand Dam to Persian Gulf with more than 450 km in length and an annual discharge of 11,891 million cubic meters, is the largest river in Iran. Increasing water withdrawal from and wastewater discharge to the river has endangered the aquatic life of this important ecosystem. Furthermore, the drinking and in-stream water quality standards have been violated in many instances. In this paper, a river water quality monitoring network is designed, including determination of sampling frequencies as well as location of water quality monitoring stations. In this regard, two models are developed. The first model is a Genetic Algorithm-based optimization model and the second one is a combination of Kriging method and Analytical Hierarchy Process. The temporal variation of the concentration of water quality variables along Karoon and Dez Rivers are evaluated and the main water quality indicators are selected. Then, thirty five stations are selected and the application of Entropy Theory in calculating the sampling frequency is demonstrated. The results show the significant value of the proposed methodology in the design of monitoring network.     

Application of network method as a tool for integrating biodiversity values in Environmental Impact Assessment

Highway construction or expansion projects are among major activities of economic development especially in developing countries. However, road development consistently can lead to major damages to the environment, including habitat fragmentation and ecological instabilities and a considerable threat to fauna and flora. At this point, Environmental Impact Assessment (EIA) in road developments is needed to address and evaluate the ecological issues in decision-making. The object of this study is to strengthen the consideration of ecological issues, i.e., biodiversity in the existing EIA tools. This paper regards a network method as a means to make informed planning decisions by the lessons from a case study. The results indicate that network method is well suited to be applied in ecological impacts assessment. However, some limitations such as complexity and time consumed make casual networks unpopular. Also, impact of traffic noise on acoustic communication (wildlife and human) was performed. It has been shown that sound level for human is much higher than admissible standards. Finally, the study expresses some mitigation measures to improve the acquisition for environmental impact assessment process.     

A review of recent developments in the application of machine learning in solar thermal collector modelling

Environmental Science and Pollution Research - Over the past few decades, the popularity of solar thermal collectors has increased dramatically because of many significant advantages like being a...     

Exposure profiles of mercury in human hair at a terai belt of North India

Human hair is frequently used as a bioindicator of mercury exposure. Mercury (Hg) has for centuries been a useful metal in a variety of applications. Unfortunately, this usefulness is counterbalanced by its neurotoxicological health impact. The US Environmental Protection Agency recommends keeping the hair Hg level <1.0 µg/g. Therefore, an investigation has been performed in order to ascertain the hair Hg levels among the people living at the terai belt of North India. Hair samples were collected from 111 individuals and were placed in an identified plastic bag, stapled to prevent the shift of the hair strand. Samples were analyzed by combustion, gold amalgamation, atomic absorption spectrometry (C-GA-AAS). The mean Hg level in hair was 0.28 µg/g for the whole group ranging from 0.0012 to 1.9091 µg/g. The mean hair Hg levels were 0.16 µg/g for men and 0.12 µg/g for women, indicating that men had higher hair Hg levels than women. Total hair Hg was found to be significantly associated with age, gender and fish consumption frequency. 98 % of the total sample had hair Hg concentrations less than 1.0 µg/g, i.e, within safe dose, whereas only 2 % had Hg concentrations greater than 1.0 µg/g, thereby exceeding the safe dose.