Screening and prioritisation of chemical risks from metal mining operations, identifying exposure media of concern

Metals have been central to the development of human civilisation from the Bronze Age to modern times, although in the past, metal mining and smelting have been the cause of serious environmental pollution with the potential to harm human health. Despite problems from artisanal mining in some developing countries, modern mining to Western standards now uses the best available mining technology combined with environmental monitoring, mitigation and remediation measures to limit emissions to the environment. This paper develops risk screening and prioritisation methods previously used for contaminated land on military and civilian sites and engineering systems for the analysis and prioritisation of chemical risks from modern metal mining operations. It uses hierarchical holographic modelling and multi-criteria decision making to analyse and prioritise the risks from potentially hazardous inorganic chemical substances released by mining operations. A case study of an active platinum group metals mine in South Africa is used to demonstrate the potential of the method. This risk-based methodology for identifying, filtering and ranking mining-related environmental and human health risks can be used to identify exposure media of greatest concern to inform risk management. It also provides a practical decision-making tool for mine acquisition and helps to communicate risk to all members of mining operation teams.     

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.     

An expert-based approach to forest road network planning by combining Delphi and spatial multi-criteria evaluation

Changes in forest landscapes resulting from road construction have increased remarkably in the last few years. On the other hand, the sustainable management of forest resources can only be achieved through a well-organized road network. In order to minimize the environmental impacts of forest roads, forest road managers must design the road network efficiently and environmentally as well. Efficient planning methodologies can assist forest road managers in considering the technical, economic, and environmental factors that affect forest road planning. This paper describes a three-stage methodology using the Delphi method for selecting the important criteria, the Analytic Hierarchy Process for obtaining the relative importance of the criteria, and finally, a spatial multi-criteria evaluation in a geographic information system (GIS) environment for identifying the lowest-impact road network alternative. Results of the Delphi method revealed that ground slope, lithology, distance from stream network, distance from faults, landslide susceptibility, erosion susceptibility, geology, and soil texture are the most important criteria for forest road planning in the study area. The suitability map for road planning was then obtained by combining the fuzzy map layers of these criteria with respect to their weights. Nine road network alternatives were designed using PEGGER, an ArcView GIS extension, and finally, their values were extracted from the suitability map. Results showed that the methodology was useful for identifying road that met environmental and cost considerations. Based on this work, we suggest future work in forest road planning using multi-criteria evaluation and decision making be considered in other regions and that the road planning criteria identified in this study may be useful.     

Optimization and Decision Heuristics for Chesapeake Bay Nutrient Reduction Strategies

Regional policies to achieve water quality goals assign a unique pollution control technology to every pollution source in a watershed, thereby defining a watershed strategy. For watersheds with even a modest number of pollution sources and control alternatives, the decision problem has combinatorial complexity. The perception of complexity—manifested in innumerable feasible watershed strategies—commonly induces the use of simplifying decision heuristics and ad hoc decision rules that reduce decision complexity by limiting the choice set to a “manageable” number of alternatives. In problems with large complex choice sets, these decision heuristics simplify decision making by excluding the vast majority of feasible alternatives a priori. In contrast, watershed-scale optimization enables decision makers to consider all feasible alternatives implicitly, exploiting rather than restricting the complexity of the feasible choice set. This contrast is illustrated using mixed-integer linear programming to identify interstate watershed strategies that achieve Chesapeake Bay nutrient reduction goals for the Potomac River Basin. The use of optimization in collaborative decision making helped refine and capture decision makers’ underlying values and preferences in policy-relevant constraints reflecting equity and political feasibility. Optimization formulations incorporating these constraints identified more effective and desirable management alternatives that would not otherwise have been considered using familiar decision heuristics and traditional comparisons among a limited number of ad hoc scenarios. Incorporating optimization in collaborative decision making generated superior watershed strategies and eased the cognitive limitations on decision making by substituting the computational burden of solving mixed-integer linear programs for decision makers’ cognitive burden of enumerating alternatives and scenarios for environmental systems with combinatorial complexity.     

Calculating of river water quality sampling frequency by the analytic hierarchy process (AHP)

River water quality sampling frequency is an important aspect of the river water quality monitoring network. A suitable sampling frequency for each station as well as for the whole network will provide a measure of the real water quality status for the water quality managers as well as the decision makers. The analytic hierarchy process (AHP) is an effective method for decision analysis and calculation of weighting factors based on multiple criteria to solve complicated problems. This study introduces a new procedure to design river water quality sampling frequency by applying the AHP. We introduce and combine weighting factors of variables with the relative weights of stations to select the sampling frequency for each station, monthly and yearly. The new procedure was applied for Jingmei and Xindian rivers, Taipei, Taiwan. The results showed that sampling frequency should be increased at high weighted stations while decreased at low weighted stations. In addition, a detailed monitoring plan for each station and each month could be scheduled from the output results. Finally, the study showed that the AHP is a suitable method to design a system for sampling frequency as it could combine multiple weights and multiple levels for stations and variables to calculate a final weight for stations, variables, and months.     

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.     

Assessment of Dust Generation Due to Opencast Coal Mining– An Indian Case Study

Every mine in India has to obtain environmental clearance fromthe Govt. Air pollution is one of the most important parametersto be considered in preparing an EIA. However, there is no welldefined method for predicting thr air pollution impact due tomining. Increasing trend of opencast (O/C) mining leads toproduction of huge quantities of dust. Emission factor data havebeen utilised to quantify the generation of dust. The projectunder study is one of the largest opencast project (OCP) forcoking coal. The main sources of air pollution have beenidentified. The rate of emission per unit of a given activityknown as an emission factor has been utilised, taking localfactors into account. It has been estimated that due to topsoilremoval, overburden (O/B) removal, extraction of coal, sizereduction generated 7.8 t of dust per day. Wind erosiongenerated 1.6 t of dust per day and the whole operationproduced dust which accounted for 9.4 mt/day. They cause airpollution in the work zone and surrouding locations. Themethodology adopted may be used to quantify generation for otherprojects also.     

Selection of suitable alternatives to reduce the environmental impact of road traffic noise using a fuzzy multi-criteria decision model

Road traffic noise is one of the most significant environmental impacts generated by transport systems. To this regard, the recent implementation of the European Environmental Noise Directive by Public Administrations of the European Union member countries has led to various noise action plans (NAPs) for reducing the noise exposure of EU inhabitants. Every country or administration is responsible for applying criteria based on their own experience or expert knowledge, but there is no regulated process for the prioritization of technical measures within these plans. This paper proposes a multi-criteria decision methodology for the selection of suitable alternatives against traffic noise in each of the road stretches included in the NAPs. The methodology first defines the main criteria and alternatives to be considered. Secondly, it determines the relative weights for the criteria and sub-criteria using the fuzzy extended analytical hierarchy process as applied to the results from an expert panel, thereby allowing expert knowledge to be captured in an automated way. A final step comprises the use of discrete multi-criteria analysis methods such as weighted sum, ELECTRE and TOPSIS, to rank the alternatives by suitability. To illustrate an application of the proposed methodology, this paper describes its implementation in a complex real case study: the selection of optimal technical solutions against traffic noise in the top priority road stretch included in the revision of the NAP of the regional road network in the province of Almeria (Spain).     

Validation of two air quality models for Indian mining conditions

All major mining activity particularly opencast mining contributes to the problem of suspended particulate matter (SPM)directly or indirectly. Therefore, assessment and prediction are required to prevent and minimize the deterioration of SPM due tovarious opencast mining operations. Determination of emission rate of SPM for these activities and validation of air quality models are the first and foremost concern. In view of the above, the study was taken up for determination of emission rate for SPMto calculate emission rate of various opencast mining activitiesand validation of commonly used two air quality models for Indianmining conditions. To achieve the objectives, eight coal and three iron ore mining sites were selected to generate site specific emission data by considering type of mining, method of working, geographical location, accessibility and above all resource availability. The study covers various mining activitiesand locations including drilling, overburden loading and unloading, coal/mineral loading and unloading, coal handling orscreening plant, exposed overburden dump, stock yard, workshop, exposed pit surface, transport road and haul road. Validation of the study was carried out through Fugitive Dust Model (FDM) and Point, Area and Line sources model (PAL2) by assigning the measured emission rate for each mining activity, meteorologicaldata and other details of the respective mine as an input to the models. Both the models were run separately for the same set ofinput data for each mine to get the predicted SPM concentrationat three receptor locations for each mine. The receptor locationswere selected such a way that at the same places the actual filedmeasurement were carried out for SPM concentration. Statisticalanalysis was carried out to assess the performance of the modelsbased on a set measured and predicted SPM concentration data. The value of coefficient of correlation for PAL2 and FDM was calculated to be 0.990-0.994 and 0.966-0.997, respectively, which shows a fairly good agreement between measured and predicted values of SPM concentration. The average index of agreement values for PAL2 and FDM was found to be 0.665 and0.752, respectively, which represents that the prediction by PAL2 and FDM models are accurate by 66.5 and 75.2%, respectively. These indicate that FDM model is more suited for Indian mining conditions.     

A Procedure for NEPA Assessment of Selenium Hazards Associated With Mining

This paper gives step-by-step instructions for assessing aquatic selenium hazards associated with mining. The procedure was developed to provide the U.S. Forest Service with a proactive capability for determining the risk of selenium pollution when it reviews mine permit applications in accordance with the National Environmental Policy Act (NEPA). The procedural framework is constructed in a decision-tree format in order to guide users through the various steps, provide a logical sequence for completing individual tasks, and identify key decision points. There are five major components designed to gather information on operational parameters of the proposed mine as well as key aspects of the physical, chemical, and biological environment surrounding it — geological assessment, mine operation assessment, hydrological assessment, biological assessment, and hazard assessment. Validation tests conducted at three mines where selenium pollution has occurred confirmed that the procedure will accurately predict ecological risks. In each case, it correctly identified and quantified selenium hazard, and indicated the steps needed to reduce this hazard to an acceptable level. By utilizing the procedure, NEPA workers can be confident in their ability to understand the risk of aquatic selenium pollution and take appropriate action. Although the procedure was developed for the Forest Service it should also be useful to other federal land management agencies that conduct NEPA assessments, as well as regulatory agencies responsible for issuing coal mining permits under the authority of the Surface Mining Control and Reclamation Act (SMCRA) and associated Section 401 water quality certification under the Clean Water Act. Mining companies will also benefit from the application of this procedure because priority selenium sources can be identified in relation to specific mine operating parameters. The procedure will reveal the point(s) at which there is a need to modify operating conditions to meet environmental quality goals. By recognizing concerns early in the NEPA process, it may be possible for a mining company to match operational parameters with environmental requirements, thereby increasing the likelihood that the permit application will be approved.     

Development and validation of rapid assessment indices of condition for coastal tidal wetlands in southern New England, USA

Desertification, land degradation in arid, semi-arid, and dry sub-humid regions, is a global environmental problem. With respect to increasing importance of desertification and its complexity, the necessity of attention to the optimal de-desertification alternatives is essential. Therefore, this work presents an analytic hierarchy process (AHP) method to objectively select the optimal de-desertification alternatives based on the results of interviews with experts in Khezr Abad region, central Iran as the case study. This model was used in Yazd Khezr Abad region to evaluate the efficiency in presentation of better alternatives related to personal and environmental situations. Obtained results indicate that the criterion "proportion and adaptation to the environment" with the weighted average of 33.6% is the most important criterion from experts viewpoints. While prevention alternatives of land usage unsuitable of reveres and conversion with 22.88% mean weight and vegetation cover development and reclamation with 21.9% mean weight are recognized ordinarily as the most important de-desertification alternatives in region. Finally, sensitivity analysis is performed in detail by varying the objective factor decision weight, the priority weight of subjective factors, and the gain factors. After the fulfillment of sensitivity analysis and determination of the most sensitive criteria and alternatives, the former classification and ranking of alternatives does not change so much, and it was observed that unsuitable land use alternative with the preference degree of 22.7% was still in the first order of priority. The final priority of livestock grazing control alternative was replaced with the alternative of modification of ground water harvesting.     

Integrated Environmental Assessment of the Mid-Atlantic Region with Analytical Network Process

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account the interdependency among variables, the method was capable of ranking ecosystems in terms of environmental conditions and suggesting cumulative impacts across a large region. Using data on land cover, population, roads, streams, air pollution, and topography of the Mid-Atlantic Region of the United States, we were able to point out areas which were in relatively poor condition and/or vulnerable to future deterioration regarding various environmental aspects. The method offered an easy and comprehensive way to combine the strengths of conventional multivariate statistics (PCA) and decision-making science tool (ANP) for integrated environmental assessment.     

Characterisation of sulphide-bearing waste-rock dumps using electrical resistivity imaging: the case study of the Rio Marina mining district (Elba Island, Italy)

Sulphide-bearing mine dumps are potential sources of pollution when acid mine drainage (AMD) occurs. Because the generation of AMD depends on the volume and composition of waste materials, their characterisation is crucial for the evaluation of geochemical hazards and for the design of remediation strategies to minimise their environmental impact. In this paper, a cost-effective strategy for the characterisation of an inactive mine dump in the Rio Marina mining district (Elba Island, Italy) using earth resistivity imaging (ERI) is presented. As no information regarding the nature of waste rocks is found in reports for the mine, five ERI profiles were acquired at the top of the waste pile. The results show that waste rocks are heterogeneous with a maximum thickness of 30 m. Due to the large amounts of dispersed sulphide minerals, the waste rocks are characterised by an electrically conductive geophysical signature in comparison to the surrounding resistive metamorphic bedrock. A geostatistical approach was adopted to estimate the elevation of the edges of the mine dump, and the net volume of the waste rocks was computed through a raster analysis of the elevations of the upper and lower boundaries of the mine dump. High-conductivity anomalies were detected within the core of the mine dump. The integration of the hydrogeological, geochemical and geological framework of the Rio Marina mining district suggests that these anomalies could be a geophysical signature of subsurface regions where AMD is currently generated or stored, thus representing sources of environmental pollution.     

采煤塌陷区水污染源解析研究

应用SPSS17.0中因子分析模型对淮南市潘一矿采煤塌陷水体常规水质指标进行污染源解析,结果得出4种主要的污染源,F1主要代表了氮磷肥引起的农业面源污染、矿井水和浅层地下水的混合污染,方差贡献率为42.991%,F2代表了矿井水污染,方差贡献率为20.180%,F3主要代表了农村污水和矿业废水混合污染,方差贡献率为13.299%,F4主要代表了煤矸石淋溶水污染,方差贡献率为11.546%。     

Assessing regional environmental quality by integrated use of remote sensing,GIS, and spatial multi-criteria evaluation for prioritization of environmental restoration

This study was an attempt to analyse the regional environmental quality with the application of remote sensing, geographical information system, and spatial multiple criteria decision analysis and, to project a quantitative method applicable to identify the status of the regional environment of the study area. Using spatial multi-criteria evaluation (SMCE) approach with expert knowledge in this study, an integrated regional environmental quality index (REQI) was computed and classified into five levels of regional environment quality viz. worse, poor, moderate, good, and very good. During the process, a set of spatial criteria were selected (here, 15 criterions) together with the degree of importance of criteria in sustainability of the regional environment. Integrated remote sensing and GIS technique and models were applied to generate the necessary factors (criterions) maps for the SMCE approach. The ranking, along with expected value method, was used to standardize the factors and on the other hand, an analytical hierarchy process (AHP) was applied for calculating factor weights. The entire process was executed in the integrated land and water information system (ILWIS) software tool that supports SMCE. The analysis showed that the overall regional environmental quality of the area was at moderate level and was partly determined by elevation. Areas under worse and poor quality of environment indicated that the regional environmental status showed decline in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate, and soil conditions have serious influence on the regional environment condition of the area. Considering the regional characteristics of environmental quality, priority, and practical needs for environmental restoration, the study area was further regionalized into four priority areas which may serve as base areas of decision making for the recovery, rebuilding, and protection of the environment.     

Integrating ecosystem services into environmental impact assessment: An analytic–deliberative approach

Analytic–deliberative techniques have been suggested as a promising approach to ecosystem service (ES) valuation but are still at an experimental stage. This paper contributes to the development of ES valuation in the environmental impact assessment (EIA) procedure by introducing an analytic–deliberative approach to assessing restoration options for a regulated river in Finland. Multi-criteria decision analysis (MCDA) with a value-focused approach was applied and compared with a desktop application of the ES-focused MCDA approach. We found out that the concept of ES could bring added value to the assessment process by: 1) enabling the framing and valuing especially of provisioning services — final ecosystem services, such as salmon catch in a more understandable way for the stakeholders, and 2) taking into account ecosystem processes and supporting services more precisely. However, some potential dangers of using the ES-based approach could include ES's appearing as a distant mode of thinking to affected groups and other stakeholders, and neglect of the trade-offs between ES and other relevant value and impact categories. Thus, although the ES framework is promising, it should not form a rigid ‘checklist’ way of making assessments but should rather be used to widen perspectives about potential issues in linking ecosystem properties to human benefits and values. It is argued that by combining the ES framework with the interactive MCDA approach, we can form a comprehensive and integrated approach to incorporating ESs into EIA.     

Assessing metal pollution in ponds constructed for controlling runoff from reclaimed coal mines

Constructing ponds to protect downstream ecosystems is a common practice in opencast coal mine reclamation. As these ponds remain integrated in the landscape, it is important to evaluate the extent of the effect of mine pollution on these ecosystems. However, this point has not been sufficiently addressed in the literature. The main objective of this work was to explore the metal pollution in man-made ponds constructed for runoff control in reclaimed opencast coal mines over time. To do so, we evaluated the concentration of ten heavy metals in the water, sediment, and Typha sp. in 16 runoff ponds ranging from 1 to 19 years old that were constructed in reclaimed opencast coal mines of northeastern Spain. To evaluate degree of mining pollution, we compared these data to those from a pit lake created in a local unreclaimed mine and to local streams as an unpolluted reference, as well as comparing toxicity levels in aquatic organisms. The runoff ponds showed toxic concentrations of Al, Cu, and Ni in the water and As and Ni in the sediment, which were maintained over time. Metal concentrations in runoff ponds were higher than in local streams, and macrophytes showed high metal concentrations. Nevertheless, metal concentrations in water and sediment in runoff ponds were lower than those in the pit lake. This study highlights the importance of mining reclamation to preserve the health of aquatic ecosystems and suggests the existence of chronic metal toxicity in the ponds, potentially jeopardizing pond ecological functions and services.     

Decision Analysis Methodology to Evaluate Integrated Solid Waste Management Alternatives

Value-focused thinking, a decision analysis technique, is used to produce a multiple-objective model that captures a site's municipal solid waste (MSW) management goals, objectives, and concerns in order to facilitate the evaluation of competing strategies. The model ranks competing MSW alternatives based on how well they meet the decision maker's strategic objective, a 20-year compliant MSW system. Sensitivity analysis is incorporated in the model to assess and illustrate the effects of changes in model objective weights and changes in model parameters. Overall, the model provides decision-makers with a decision tool to make a better decision when choosing a new MSW management strategy. The entire process is applied to a case study using Earekson Air Station, a remote U.S. Air Force installation.