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4.1 Work plan, deliverables and load balancing

4.1.1 Approach: selection of study sites

Figure 3 one below present the scale issues of the approach for producing the innovative environmental services and the ecotechnology. The green color of the compartment for large scale circulation of toxic substances by water indicated that this is solved from the point of view of available environmental services (using commercial or open access models like Modflow, WMS, CAESAR-Tracer). Workpackages 1 and 2 deal with tailing dams, relatively small scale. Some of the activities in WP2 are done at the scale of small catchments having taling dams in their structure (identification of native plant species for remediation). WP3 deals with downscaling the inputs from large scale transport model to small scale in the groundwater systems of contaminated floodplains. WP 4 deals with downscaling and/or upscaling the concentrations of toxic elements in the sediment of contaminated floodplains to the scale relevant for the interception of toxic elements by target natural organisms or human organizations. Also WP4 deals with multiple scale issues like the optimization of monitoring system of toxic elements in all parts of the river basin (S4), and assisting the stakeholders for linking their environmental management plans with respect to the effects due to the fluxes of transported toxic elements from mining areas downstream.

Figure 3 The structure of the approach with respect to the scale of investigated systems in contaminated river basins. S1-S5 = innovative environmental services as described in table 1, T1 = innovative ecotechnology.

The tailing ponds in Romania contain big quantities of heavy metals and rare earths because of old extraction techniques that used to have low recovery rates. This makes the neutralization of the waste material from the tailing ponds a very difficult and expensive operation. An efficient alternative appears to be the extraction of those heavy metals. This way, the exploitation of tailing ponds for recovering the elements contained in big quantities becomes not only a viable method for obtaining metals, but also a method that can lead to their remediation and can also be financial self-sustainable. The remaining material will have considerable less content of heavy metals, and by additional operations using geochemical and biological techniques they will be transformed into an inert material for the environment, placed in a new location properly chosen with modern investigation techniques.

The evaluation of the stocks and forms of metals in tailing ponds is useful both for the hazard assessment and their eventual re-exploitation, and it will be tackled by Objective 1 of the project. The estimation methodology has to be cost-effective, time-effective and precise.  We propose for volume calculation an approach using near-surface geophysical methods, for the stock and forms of metals mathematical models correlating the geochemical and mineralogical parameters of the tailing material with geophysical parameters.

Once taken the decision for the re-exploitation or direct remediation of the tailing pounds the remediation solution should be designed.  We propose an approach involving a mixing of the tailing material and amendments and the use of native plant species already present in the surrounding and on the taling pond (Neagoe et al. 2005, Iordache et al 2010), and microbial consortia extracted from the tailing material (adapted to local conditions), with experimental and field experiments.

The selection of study sites for WP1 and WP2 (figure 4) allows the combination of different geomorphological and hydrological settings, different climates and different ecosystems which will allow the integration into a scheme of remediation actions that are site-specifically optimized and yet allow generalized application for different regions across Europe.

Figure 4 The studied sites for WP1 and WP2 in TIMMAR.

Each site will be approached (Table 3) at two hierarchical levels: ecosystem (contaminated land), and the integrating low order catchment. The interface between the three main influencing components (plant ecology, geology, and modelling) will be defined and integrated for a general understanding of ecosystem and landscapes function in the process. A general overview of the activities involved can be seen in the Gant Pert diagram of the project (chapter 4.2).

Table 3 Types of approaches of the studied systems

At tailing pond scale a correlation of geophysical, geochemical and mineralogical parameters will be performed. The resistivity surveys will be performed using the vertical electrical soundings method (VES) using a Schlumberger type array, with an ABEM SAS1000 Terrameter system belonging to UB. On each of the 4 tailing ponds a grid of measuring points will be constructed. Depending on their surface, the grid will have particular characteristics. On medium size tailing ponds like Teliuc no. 2 (15 ha), Valea Mealu (20 ha) and Plopis-Rachitele (14 ha), the grid will have cells of 50 x 50 m, the data collecting stations being placed in the nodes of the grid. Two cells of 50 x 50 m will be selected for a detailed investigation, following grids of 10 x 10 m inside the selected cells. On the Brezesti tailing pond (6 ha in surface) the main grid will have cells of 20 x 20 m. Two squares of 20 x 20 m will be selected for detailed investigation, following grids of 5 x 5 m inside the selected cells. The investigation depth will vary between 10 – 80 m, depending on the possibilities of extending the injection electrode lines. All the collected data will be georeferenced and integrated into the project’s database. The geophysical data acquisition will require field camps and typical materials to be used in the field: protection equipment, wooden sticks, ropes, tape measures, stationery.

Raw data processing. The resistivity data will be analyzed and processed in order to obtain apparent and inversion resistivity sections. The primary processing of the raw data will be realized using Matlab codes designed by UB team, while the empirical correction of the VES curves will be conducted in Microsoft Excel. Apparent resistivity sections will be computed by interpolation, having as entry data the filtered apparent resistivity values obtained. The interpolation method will be the Triangulation with Linear Interpolation method, which uses the optimal Delaunay triangulation. The algorithm creates triangles by drawing lines between data points. The original points are connected in such a way that no triangle edges are intersected by other triangles. The result is a patchwork of triangular faces over the extent of the grid. This method is an exact interpolator. The interpolation and the imaging of the data will be realized using the software Surfer 8 (by Golden Software). Inverse modeling will also be applied on the apparent resistivity data. The 1D inversion will be applied using the IPI2Win software, the 1D inversions being constrained with the information already available regarding the tailing pond depth and the observations on the apparent resistivity curves and sections. The data data will also be processed by means of the RES2DINV modeling software in order to perform 2D geoelectrical data inversion. The inversion routines are based on the smoothness-constrained least squares method and the forward resistivity calculations were executed by applying an iterative algorithm based on a Finite Element Method (FEM). 2D inversion sections of real resistivity data will be obtained. UB owns licenses for all the software used for this activity, excepting IPI2Win which has a freeware license. Excepting stationery, the data processing activity won’t involve other type of resources.

For geochemistry a nested surface grid will be adopted, coupled with drilling (table 4 below). The geochemical sampling will be done by P1. The surface sampling realize by the UB team will require: field camps expenses, protection equipment, materials (plastic bags, wooden sticks, stationery, sampling tools).

Table 4 Sampling intensity by tailing pond.

The geochemical analyses will be realized at the Prospectiuni SA Laboratories. The global geochemical analyses use Indusctively Coupled Plasma (ICP) and X-Ray Fluorescence (XRF) techniques to measure the concentrations selected elements in each sample. ICP-MS and ICP-AES geochemical analysis will be executed on the collected samples for the following elements: Au, Ag, Pb, Zn, Cu, Se, Te, As, Li, Be, B, Cd, Sb, Ta, Ti, Zr, Ge, W, Mo, Co, V, In, Nd, Nb, Re, Ga, Hf and the following oxides: SiO2, TiO2, Al2O3, Fe2O3, MnO, MgO, CaO, Na2O, K2O şi P2O5. A number between 150 – 200 samples will be subject to Sequential Extraction Procedure (SEP) investigation (Tessier 1979). A 5 step procedure will be applied in order to isolate the fraction with mineral phases that have not been affected by the oxidation processes, with a specific interest manifested to sulfides. The residual fraction from this procedure will be transferred to the UB laboratories for mineralogical investigation.

The mineralogical study will approach the mineralogical description of the samples and will be integrated with granulometrical and sequential analyses. The mineralogical phases will be identified throughout the optical mineralogy and X-Ray Diffraction (XRD). The optical study will be realized in reflected and transmitted light, using microscopes Nikon E400-POL and Olympus BH2-UMA. Laboratory consumables will be required to realize the polished and thin sections for 500 samples: all the 400 samples collected from drills and 100 samples collected from the surface grids. The XRD analyses will be realized in powder with a X’Ppert PANalytical instrument (CuKα target diffractometer) at the UB laboratories. The same samples will be chosen for investigation as in the case of optical study. The XRD analysis involves costs for water filters. The optical and XRD tests will offer qualitative and quantitative estimation for mineral contents for the investigated samples. A number of 40 samples will be selected from drills for granulometric separation. Optical analysis and XRD will be realized on the separated phases, for correlation of the mineralogical phases with the particle size distribution.

2 D and 3D mapping of stocks, forms and control parameters of metals mobility. Firstly, the apparent resistivity sections will be interpreted using the drilling observations and the 1D inversion models. Integrating the interpreted apparent resistivity sections and the 2D inversion resistivity sections, geophysical models will be realized for the investigated objectives. The first goal of this activity is to identify for each tailing pond the contact between the waste dump body and the natural formations. An image representing the paleo-topography of the valley before it was filled will result after the interpolation of the obtained results after the integration of the resistivity data and the information from drills). Subtracting the corresponding grid for the topographical surface and the grid representing the paleo-topography of the valley, a thickness map will be obtained and based on this, the volume of the waste dump body will be calculated. Studies show that, in tailing ponds, the oxidation layer can be separated from the reduction layer using geoelectric investigations (Iacob 2011). Integrating the 1D inversion results with the results from the geochemical investigation (pH measurements, sequential extraction to emphasize the oxidation degree) will help developing in detail this theory and will help evaluating its applicability. The limit of the oxidation layer will be identified and its volume will be calculated in a similar matter as the tailing pond’s volume. As a consequence, the reduction layer will be considered the rest of the tailing pond. The metal stocks on the tailing ponds have to be calculated with respect to the anisotropy of the geochemical composition of the tailing pond, namely to the identified oxidation and reduction volumes. Tailing ponds have a vertical oriented direction of the maximum anisotropy, being constituted of thin horizontal layers deposed by elutriation between the successive dumpings of the tailing material. Thus, metal content means will be calculated for depth intervals. Studies show that tailing ponds have also a horizontal anisotropy, caused by construction procedures or post-depositional geochemical processes. Using the latest advances in resistivity surveys, the homogenous and anisotropic volumes can be emphasized on a tailing pond. According to the horizontal anisotropy sections, areas of homogeneity have to be delimitated, and weighted means of metal contents will be calculated for each depth interval depending of these areas. The predictive metal distribution will be computed using the Kriging interpolation method. All the above operations have to be executed separately for the oxidation and reduction volumes, the total metal stock being represented by the summation of the values obtained for the two volumes for each selected element of interest. The mineralogical forms’ distribution will be obtained extrapolating the results of the mineralogical investigation using the same procedure used for the metal stocks. The 3D distribution model in metal contents and mineralogical forms will be obtained from the collection of the georeferenced 2D distribution models. This activity will require only stationery resources. The parameters that characterize the metals mobility within the tailing pond are the mineralogical phase transformation that release metals into the interstitial water and transport parameters which can be characterized by the hydraulic parameters. Our methodology is based on the analysis of resistivity data, resistivity parameters such as Dar-Zarrouk (D-Z) parameters, and their application in quantitative estimations of the hydraulic parameters.

Statistical analysis of geophysical and geochemical data will be done using geophysical and geochemical methods and geostatistical analyses (Fachinelly 2000), we will provide an advanced surface modeling generated using ESRI ArcGis Geostatistical Analyst (ESRI Redlands, California SUA), which can be used in geographic information system (GIS) models. Geostatistical tools can be integrated within GIS modeling environments. The purpose of this activity is to perform an evaluation of the statistical properties of the observed geophysical and geochemical data such as spatial variability and spatial data dependence. The final product will be a conceptual geochemical model in which both oxidation and reduction regions will be characterized, meaning spatial distribution and chemical behavior. The quality of the models will be quantified by measuring the statistical error of predicted surfaces. This activity will require only stationery resources.

For the data base of plants (P2) in the catchment we will use maps of the vegetation and characterize the following parameters: ecosystems/habitats type and distribution, vegetation/habitat status. Stability of the vegetation and percentage of natural cover, exposure of bare (un-vegetated) soil for more than 15% of an area provides a guide for poor condition, populations diversity of key plant species and spatial patterning of plant populations. For the ecological characterization of field plots  we will make use of species list, Braun-Blanquet method, Ellemberg indices or national indices (UTR), species lifespan, clonal status.

In order to develop the plant promoting microbial consortia (CO-Biocehmistry), microbes will be identified and characterized for their use in planting regimes to test for bioaugmentation in remediation actions. To achieve this goal different microbial communities will be isolated for all four mine tailing, using specific techniques and the experimental protocols according with UMBRELLA FP7 project.The production of the bacterial inoculum will have the following steps:

1. Isolation of microbial communities from the contaminated sites (samples will be taken from 100 different spots, based on soil structure, composition and contamination range).

2. Selection of the hyper-tolerant or/and hyperaccumulating strains (milestone).

3. Taxonomic identification of the candidate strains selected in Task 2 (identification will be done by BLAST analysis of the 16S rRNA sequence; for this, rRNA will be pre-amplified by Reverse Transcriptase-PCR and sequenced).

4. Optimization of  growth, storage and transport conditions for the strains identified  in Task  2.

5. Identification of the most cost-effective conditions for amplification, storage,  and in field inoculation

6. Utilization of candidate strains in field condition

7. Assessment of bioremediation capacity.

Field experiment with native species and substratum optimization - design and analyses (CO-CESEC). Germination experiments experiment will be run in 15 different experimental variants and 5 replicates each using one dominant native plant species, leading after coupling with field data processing to the indentification of appropriate species. Using results from WP1 two tailing dams (acidic and alkaline pH) will be selected for field experiments. On each of the two selected mine tailing will be run 25x2 plots (2x2 m) representing a negative control and 4 experimental variants (in 5 replicates) with inoculations and/or amendments like: arbuscular mycorrhyzal fungi (AMF), expanded clay, top soil, plant growth promotion rhyzobacteria (PGPR), limestone, zeolite, mineral compost, green manure,  mixed in different combinations in function of the geochemical characteristics of the tailing material. These experiments will be run for a period of one year with three sampling times each of them, leading to a total of about 300 samples of substrate and 600 samples of plants (above- and underground part). The parameters measured will be for substrate: soil moisture, pH, EC, LOI, soil respiration, N, P and S extractable forms, P total, heavy metals (HM), sequential extractions (only mobile fractions) (according with Zeien and Brümmer, 1989) and soil granulometry. For plants: aboveground and underground biomass (fresh and wet), number and height of individuals; physiological plant observations regarding with their vitality such as photosynthetic activity, blooming etc., HMs in aboveground (divided on plant parts where is necessary) and underground biomass, P total forms, oxidative stress, enzymatic and non enzymatic activity such as superoxide dismutase activity (SOD), peroxidase activity (POD), TBA lipid peroxidation, protein and assimilating pigments (Neagoe et al. 2004, 2005, 2006).

The evaluation of long distances effects of the tailing ponds in the floodplain groundwater involves the use of existing numerical models of the groundwater flow and contaminant transport. A major disadvantage is that this approach does not take into account the small scale heterogeneity of contamination in both soil and groundwater, very important for the prediction of the risk at small scale. In unconsolidated sediments the variation of the hydraulic parameters is controlled mainly by the lithological heterogeneities. These are a product of the depositional and transport processes which took place within the fluvial system (Kostic et al., 2007).

At field crop and groundwater well scale, relevant for each private stakeholder downstream mining areas, we propose an innovative cost-effective approach, which involve the use of high resolution geophysical methods (Ground Penetrating Radar and DC Resistivity), coupled with direct hidrogeological and sedimentological investigation techniques.

The geophysical surveys will be performed using the ABEM SAS1000 Terrameter System and the GSSI SIR 3000 System with three different types of antennas (100, 200 and 400 MHz), both belonging to the UB. For each of the two hydrographical basins (Ampoi and Aries) five small scale geomorphologic reaches will be chosen, so that every of them is located in the vicinity of an inhabited area. On each of the chosen geomorphologic reaches, a grid of measuring points with different characteristics will be constructed. All the geophysical measurements will be performed within these grids. All the collected data will be georeferenced and integrated into the project’s database. The geophysical data acquisition will require field camps and typical materials to be used in the field: protection equipment, wooden sticks, ropes, tape measures, stationery.

For each of the chosen geomorphologic reaches, both a hydrogeological balance and a hydrochemical characterization will be performed. A network of piezometers will be placed in each analyzed sector with the aim to monitor the groundwater level. Water samples will be prevailed from both the existing groundwater wells and from the installed piezometers, in order to perform the hydrochemical characterization. The punctual information resulted from the direct hydrogeological methods will be extended through the use of resistivity investigation. Therefore, for each of the investigated sites, a 3D image of the aquifer’s geometry will be emphasized. Also, hydrogelological parameters such as hydraulic conductivity and natural protection capacity will be estimated (Orza, 2011, 2012; Henriet, 1976).

The sedimentary architecture characterization will be performed in the areas where outcrops exist, with the aim to highlight the lithofacieses and the depositional elements. For each lithofacies class recognized in the analyzed outcrops the dominant grain size will be established through granulometric analysis. Also, for each class, other elements (texture, fabric, stratification, degree of clast rounding) will be described directly in the field.

The 3D extent of the main depositional elements associated with the identified lithofacieses will be described through the application of high resolution geophysical methods such as Ground Penetrating Radar (GPR) which can offer us the possibility of emphasizing the heterogeneities within the fluvial deposits (Orza et al., 2013; Lunt et al., 2004). The hydraulic properties are controlled directly by the sedimentological features. The water flow is directed toward the interconnected depositional elements with a high degree of permeability. Therefore, having a 3D image of the heterogeneities distribution at a small scale within the fluvial system can lead us to the possibility of creating downscaling models for metals in groundwater, which can be further coupled with existing transport models in order to quantify the effects of metals export from mining areas at a relevant resolution for the individual stakeholder.

The studied areas will be the same contaminated floodplain reaches as in WP3. The tools produced for supporting innovative environmental services are ment to be coupled with existing toxic elements transport models by river water and groundwater (green box in figure 3). Each floodplain reach will be fully characterised by hydrogeomorphic and soil parameters and landscape parameters (neighbouring landscape units, distance from river, etc). Sampling of soil (stratified cluster experimental approach adapted from King et al. 2004). A field-XRF (Niton) will be used for mapping in situ the metals and corrected maps will be generated using regression equations between the concentration determined in the field and ICP-MS measurements on a sub-set of samples. Soil will be sampled for of total and extractable N and P, pH, EC, CEC, soil granulometry, sequential extractions (the two most mobile fractions Zeien and Brümmer, 1989), total metals (by ICP-AES and ICP-MS) and loss on ignition (LOI).

The information system will be organized in Arc-Info. Beside usual interpolation methods and spatial analysis at the investigated scales, experimental and field data sets will be used for the production of bioaccumulation models. In order to set up the nonlinear correlation models, the software packages MATLAB and Statistica will be used. The models developed based on the experimental data will be done code programming (EDN - ESRI development network).

The innovative environmental service 3 will be based on the transfer functions for down-scaling or up-scaling to the scale of target organisms and organisations will relate the statistical parameters of the distribution and the spatial patterns of distribution with intrinsic and relational parameters of the floodplain reach and smaller units at the resolution of the grid used for sampling. The first step will be to establish the size of the bioaccumulation areas for natural organisms according to the literature on species ecology, and the size of the management units of land owners or administrators in the studied landscapes.

Downscaling tools usually are based on continuous statistical distribution functions of the downscaling parameter in space. Our point is to produce downscaling procedures for discrete distributions linking average concentrations estimated at precise scales imposed by the nature of the phenomena (retention, bioaccumulation, ecotoxicological effects). Let CL be the average concentration of metals in soil in a riparian landscape having the scale of 0.1-10 square kms, and CSPUi with i from 1 to n the concentrations at scales relevant for the bioaccumulation of metals in specific groups of plants (100 to 1000 square meters), and at scales relevant for the describing the effects of elements on the functioning of a services providing unit (10000 meters). Donwnscaling CL to CSPUi is a problem of producing to types of models: 1) one predicting the empirical distribution histogram of the CSPUi which by simple average would lead to CL (i.e. predicting the range of downscaled concentrations and the number of occurrences for each frequency class), and 2) a model linking downscaling CSPUi values with a spatial location, or with other parameters with known spatial value at CSPUi scale (these can be internal to the riparian area, or landscape parameters putting parts of the riparian area in the context – e.g. distance to river, distance to pollution source).  Type 1 models will result from the empirical study of elements distribution in the discretization units of the floodplain reach and classification of the empirical histograms by riparian area types. Type 2 models will consist in a deterministic component and a stochastic component, reversing the idea from kriging techniques. The deterministic component will be in terms of multiple regression models giving account of part of the CSPUi variance in function of internal and landscape parameters (as resulted from the empirical study), while the residual variance will be described by a function fitting the empirical histogram describing obtained in type 1 models.

Up-scaling the concentrations of toxic elements from the discretization units of the transport models to that of large organisms will need first of all a synthesis of behavior ecology knowledge relevant for the use of landscape habitat by organisms (e.g. as in the case of BERISP model, http://www.berisp.org/ ). From a technical point of view want we have to do is to produce the contamination input data for such ecotoxicological models. The tool will allow the for coupling of transport model with existing bioaccumulation models, and thus an as good as possible risk and impact assessment of upstream management measures in mining areas on downstream biodiversity. The approach will be similar as in the case of downscaling tools, but the variables used in modeling will be different, reflecting the characteristics of the habitats relevant for the target species.

Up-scaling to the scale of land management units will be approached by an empirical analyses of land use and property limits in the investigated areas and by usual statistical approaches for estimating the average concentrations of metals to which the crops or pastures are exposed.

After the mathematical model will be performed a decision support system in the form of a software platform with user friendly interface will be designed. The interface will be constructed constrained by the information on stakeholders capabilities and needs.

A populations of representative stakeholders from the list obtained in WP5 will be interviewed and data on their organizational characteristics and environmental management policies,  concerns and needs will be analyzed by P1. Potential funding sources for buying TIMMAR environmental services for answering their needs will be inventoried and disseminated to the stakeholders in WP5, but this information will also be used for conceiving the marketing form of the environmental services in a way compatible with the language and perception of the stakeholders (although the same mathematics will be behind).

The results of the organizational analyses will point out also the kind of data needed by each user, and implicitly the environmental monitoring needs. The interest and/or openness in cooperating with other stakeholders from the contaminated catchments in order to have economies of scale in the purchase of needed data will be characterized for each stakeholder type. Based on these investigations the possibilities for optimizing and coupling monitoring systems of polluters and polluted stakeholders will be identified (innovative service 4). Innovative service 5 will target 1) the potential for obtaining jointly public (European) funding for solving problems due to contamination with toxic elements in partnership consortiums of stakeholders, from bilateral projects to projects for constructing virtual workshops for the whole forum of stakeholders in a basin, and 2) the potential for buying other TIMMAR environmental services in consortiums of stakeholders in order to reduce the purchasing costs.

The University of Bucharest will be the coordinating institution. The coordinator has longstanding experience in a large number of national and international projects. This will be backed by financial, legal and logistical support from the University administration.

TIMMAR is a transdisciplinary project composed of highly complementary research, development. As an aid to organize all these aspects into a coherent project that will ensure success and maximum exploitation, the various tasks are grouped into two horizontal work packages, and two cross-cutting work packages and one combinatory work package. The experience led us to propose a management that is sufficient to oversee the project as a whole and to allow excellent output, but at the same time keep it as slender as possible without the implementation of excess structures to ensure viability of the project.

The work-package for management will be implemented by the University of Bucharest. The resources for management comes from two sources: the budget of the „Management and scientific coordination” activities and the overhead costs of the University of Bucharest (30% of these overheads go the research centers involved in the project, part of which will be used for the management of the project – meetings, web page, public image of the project, etc.).

We choose to combine the tasks essential for the daily management on one place with the Coordinator. All WP speakers are in close contact and will meet as often as necessary. The website of the consortium with the “virtual desk” option will be structured such as to allow easy access to all data by every partner and PhD student, such that the management of the work packages can be easily overseen by the speaker of each work-package.

The project coordination committee includes the same persons that are constituting the WP management, namely the speakers of the work packages 1 to 4, and the manager to be appointed for the project. In order to ensure scientific and coordination quality management, an advisory board is implemented. This will consist of all key persons of the project and experts from The Agency for Mineral resources.  In order to facilitate the closest possible contact, these persons will also be invited at the summer schools and faculty symposium held each year at UB.

The project office will be headed by the manager; this part is concerned with the organizational and financial questions that will arise during the project and will also be responsible from the coordination with the documentation necessary for patenting the results. An ombudsman for questions of conduct, for questions arising from the PhD students, and on all questions of best practice will be elected by the general assembly. This person should not be the coordinator. The general assembly also will take place yearly after the symposium of the faculty of geology, UB. The use of one specific meeting for all questions of management ensures that decisions from one committee will be easily explained to the others and also allow for the best time management. Thus, the general assembly will meet once a year.

Fiscal Management will be in the responsibility of the project director at the University of Bucharest, who will control the allocation of the contributions received from the UEFISCDI and follow the recommendations given by the project officer. It verifies the expenditures planned and incurred by the TIMMAR partners according to the UEFISCDI rules laid out in the contract. It will also contribute a special section to the IT management with the “virtual desk” platform to provide transparent and up-to-date information to all project partners of the distribution of funds.

The financial part of coordination will be aided by the Financial Department of the University. They will help the manager with timely, professional compliance with national regulations from the project officer, focusing on scientific and financial reporting requirements as well as logistical coordination of research, development, training, and dissemination activities. The manager is devoted to managing various kinds of scientific, financial, legal and logistic tasks. Experienced staff (paid from the recurrent budget of UB) is already available and familiar with TIMMAR, as they have assisted in preparing the TIMMAR proposal.

The manager position will be advertised and filled with regard to the standards in scientific and applied management skills (formal training in project management requested).

The general contact between members is also facilitated by the fact that field trips are organized for all partners to all field sites. At these occasions the partners and employed PhD students or research staff will meet and also be able to discuss management strategies. For a visual presentation of the management structure see Figure in chapter “Structure of the consortium”.

Significant risks or contingency plans

Risks associated with managing and controlling an ambitious endeavor such as TIMMAR have been minimized by the project’s organizational structure, and the history of long standing successful scientific collaboration of the TIMMAR partners. All partners have already collaborated and been to the national and international meetings in previous years and have co-authored articles and books to establish the personal contact which generally is the best possible basis for solving potential future problems arising within a large community in collaborative projects. The partners all have experience in several bilateral or multi-partner projects.

The risks associated with the TIMMAR project can be divided into two classes: Risks related to the scientific activities of the research program and risks related to the transfer of the scientific results into applications (the deliverables of the project). Scientific risks are minimal because all partners have been selected on the basis on their previous successful scientific work in the area they are contributing to and integrating in TIMMAR. Application risks are also minimal because of the great interest in our products as proved by the letters of interest from private and public end-users.

A major risk manifested in the previous project was related to the long term access to tailing dams for experimental works. This is now eliminated by direct support from the government agency responsible for their management. A reserve solution for the activity of microbial community description and consortium preparation is to externalize this activity to European partners involved in common FP7 projects. We preferred to keep it within Romanian partners in order to have full intellectual property right on the eco-remediation technology resulted from the project.

A table summarizing all the project deliverables will be provided below.