Decision support methods for the environmental assessment of contamination at mining sites

Polluting mine accidents and widespread environmental contamination associated with historic mining in Europe and elsewhere has triggered the improvement of related environmental legislation and of the environmental assessment and management methods for the mining industry. Mining has some unique features such as natural background pollution associated with natural mineral deposits, industrial activities and contamination located in the three-dimensional sub-surface space, the problem of long-term remediation after mine closure, problem of secondary contaminated areas around mine sites and abandoned mines in historic regions like Europe. These mining-specific problems require special tools to address the complexity of the environmental problems of mining-related contamination. The objective of this paper is to review and evaluate some of the decision support methods that have been developed and applied to mining contamination. In this paper, only those methods that are both efficient decision support tools and provide a ‘holistic’ approach to the complex problem as well are considered. These tools are (1) landscape ecology, (2) industrial ecology, (3) landscape geochemistry, (4) geo-environmental models, (5) environmental impact assessment, (6) environmental risk assessment, (7) material flow analysis and (8) life cycle assessment. This unique inter-disciplinary study should enable both the researcher and the practitioner to obtain broad view on the state-of-the-art of decision support methods for the environmental assessment of contamination at mine sites. Documented examples and abundant references are also provided.     

A combined frequency–severity approach for the analysis of rear-end crashes on urban arterials

Analysis of both the crash count and the severity of injury are required to provide the complete picture of the safety situation of any given roadway. The randomness of crashes, the one-way dependency of injury on crash occurrence and the difference in response types have typically led researchers into developing independent statistical models for crash count and severity classification. The Genetic Programming (GP) methodology adopts the concepts of evolutionary biology such as crossover and mutation in effectively giving a common heuristic approach to model the development for the two different modeling objectives. The chosen GP models have the highest hit rate for rear-end crash classification problem and the least error for function fitting (regression) problems. Higher Average Daily Traffic (ADT) is more likely to result in more crashes. Absence of on-street parking may result in diminished severity of injuries resulting from crashes as they may provide “soft” crash barrier in contrast to fixed road side objects. Graphical presentation of the frequency of crashes with varying input variables shed new light on the results and its interpretation. Higher friction coefficient of roadways result in reduced frequency of crashes during the morning peak hours, with the trend being reversed during the afternoon peak hours. Crash counts have been observed to be at a maximum at a surface width of 30 ft. Sensitivity analysis results reflect that ADT is responsible for the largest variation in crash counts on urban arterials.     

Feasibility study of rainwater harvesting system in Sylhet City

In rural areas in Bangladesh, groundwater is the principal source of water supply. This underground water is available in considerable amount in shallow aquifers. It is free from pathogenic microorganisms and hence water-borne diseases. In plain lands, other than hilly areas, water supply to 97% rural population comes from tube-wells, which is regarded to be a phenomenal achievement in preserving public health. Besides, a dependable water supply system all throughout the country is offset by two factors: (a) high salinity in surface plus groundwater in coastal areas; (b) want of suitable groundwater aquifers in hilly areas and the high cost of setting up tube-wells due to deep underground water table and stony layers. However, presence of arsenic in underground water now poses a serious threat to the success once made in water supply by setting up of manually operated tube-wells in the village areas—the achievement is now on the brink of total collapse. In about 61 districts out of 64, presence of arsenic exceeds a quantity of 0.05 mg/1, a permissible limit as per Bangladeshi water quality standard. Harvesting rainwater can be a pragmatic solution to this problem, which is common in many places in Sylhet especially in the hilly areas on the north eastern part of the city. This can be an alternative source of drinking water because of availability of rainwater from March to October. Heavy rain occurs from end of May till mid September, which is commonly known as the rainy season. This paper focuses on the possibility of harvesting rainwater in rural communities and thickly populated urban areas of Sylhet. It also demonstrates the scopes of harvesting rainwater using simple and low-cost technology. With setting up of a carefully planned rainwater storage tank, a family can have all of its drinking water from rain. Planned use of rainwater through rainwater harvesting in the roof catchments may fulfill the entire annual domestic water demand of a family in the rural areas of Bangladesh.     

Assessment of sediment quality in the Mediterranean Sea–Boughrara lagoon exchange areas (southeastern Tunisia): GIS approach-based chemometric methods

Concentrations of selected heavy metals (Cd, Pb, Zn, Cu, Mn, and Fe) in surface sediments from 66 sites in both northern and eastern Mediterranean Sea–Boughrara lagoon exchange areas (southeastern Tunisia) were studied in order to understand current metal contamination due to the urbanization and economic development of nearby several coastal regions of the Gulf of Gabès. Multiple approaches were applied for the sediment quality assessment. These approaches were based on GIS coupled with chemometric methods (enrichment factors, geoaccumulation index, principal component analysis, and cluster analysis). Enrichment factors and principal component analysis revealed two distinct groups of metals. The first group corresponded to Fe and Mn derived from natural sources, and the second group contained Cd, Pb, Zn, and Cu originated from man-made sources. For these latter metals, cluster analysis showed two distinct distributions in the selected areas. They were attributed to temporal and spatial variations of contaminant sources input. The geoaccumulation index (I _geo) values explained that only Cd, Pb, and Cu can be considered as moderate to extreme pollutants in the studied sediments.     

Filtering effect of wind flow turbulence on atmospheric pollutant dispersion

This paper presents a model for coupling the statistics of wind velocity distribution and atmospheric pollutant dispersion. The effect of wind velocity distribution is modeled as a three-dimensional finite-impulse response (3D-FIR) filter. A phase space representation of the 3D-FIR filter window is discussed. The resulting pollutant dispersion is the multiplication in the phase space of the 3-D Fourier transform of the pollutant concentration and the volume described by the filter window coefficients. The shape of the filter window in the phase space enables representing such effects as vortex shedding thermal currents, etc. The impact of spatial distribution of the sensors on the resulting pollutant spatial distribution and the 3-D FIR filter model employed also discuss. The case of a neutrally buoyant plume emitted from an elevated point source in a turbulent boundary layer considers. The results show that wind turbulence is an important factor in the pollutant dispersion and introduces expected random fluctuations in pollutant distribution and leads to spreading the distribution due to wind mixing.     

Assessing health impacts in complex eco-epidemiological settings in the humid tropics: Modular baseline health surveys

The quantitative assessment of health impacts has been identified as a crucial feature for realising the full potential of health impact assessment (HIA). In settings where demographic and health data are notoriously scarce, but there is a broad range of ascertainable ecological, environmental, epidemiological and socioeconomic information, a diverse toolkit of data collection strategies becomes relevant for the mainly small-area impacts of interest. We present a modular, cross-sectional baseline health survey study design, which has been developed for HIA of industrial development projects in the humid tropics. The modular nature of our toolkit allows our methodology to be readily adapted to the prevailing eco-epidemiological characteristics of a given project setting. Central to our design is a broad set of key performance indicators, covering a multiplicity of health outcomes and determinants at different levels and scales. We present experience and key findings from our modular baseline health survey methodology employed in 14 selected sentinel sites within an iron ore mining project in the Republic of Guinea. We argue that our methodology is a generic example of rapid evidence assembly in difficult-to-reach localities, where improvement of the predictive validity of the assessment and establishment of a benchmark for longitudinal monitoring of project impacts and mitigation efforts is needed.